understand

name	understand
description	[Process] Use when the developer wants something explained — by default the current working tasks + changes in context, or whatever the prompt names (a plan, a subsystem, a decision, a concept, a bug). AI derives WHAT to explain from the prompt and ALWAYS delivers a detailed, one-way explanation of purpose (why it exists), how (the mechanics), and why-this-way (trade-offs/alternatives) — regardless of coding level. Never asks the user questions, never quizzes, never blocks.
disable-model-invocation	false

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex uses static project-reference loading instead of runtime-injected project docs. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Missing/stale context route: If docs/project-config.json, the docs index, lessons.md, CLAUDE.md, AGENTS.md, or any task-required reference doc is missing or stale, auto-run $project-init or the narrow setup route ($project-config, $docs-init, $scan-all, $scan --target=<key>, $claude-md-init) before ordinary project-specific work. If Codex mirrors or AGENTS.md are missing/stale, ask the user to run $sync-codex; do not auto-run it.

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec authoring, docs/specs/ pathing, or TC format: feature-spec-reference.md, spec-system-reference.md, spec-principles.md
• Behavior/public-contract changes or spec-test-code sync: workflow-spec-test-code-cycle-reference.md plus the spec docs above
• Derived spec indexes/ERDs/reimplementation guides: spec-system-reference.md and source Feature Specs under docs/specs/
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Leave the developer carrying genuine, traced understanding of whatever matters right now — so AI accelerates the human without eroding their grasp of the codebase — by always delivering a clear, detailed, one-way explanation of WHAT it is, its PURPOSE (why it exists), HOW it works (the mechanics), and WHY this way (the trade-offs and rejected alternatives). AI derives WHAT to explain from the user's prompt. There are no fixed modes — the scope flexes to whatever the developer needs explained, and the explanation is given in full regardless of the developer's coding level — never skipped, never gated.

Scope is prompt-driven — flexible for all cases:

• Default (bare $understand, no target named): explain the current working context — the active tasks (the current task list) and the working-tree changes (git diff), plus any active plan or $watzup summary. "Here's what we're working on, what changed, and why."
• Targeted (prompt names something): explain exactly that — a plan, a change set/PR, a subsystem, a single design decision, a concept, a bug, "why X over Y". Read the prompt, derive the target, gather only that material.
• Ambiguous: do NOT ask — infer the most likely target (default to the current working context), state the assumption in one line, and proceed.

Key Rules (the contract — read these first):

• DERIVE SCOPE FROM THE PROMPT. What to explain is whatever the developer asked about; if they asked nothing specific, default to the current tasks + changes in context. Never force a fixed agenda.
• ALWAYS EXPLAIN IN FULL — REGARDLESS OF CODING LEVEL. Always cover purpose, how, and why in detail. Coding level only tunes vocabulary and analogy density (ELI5 ↔ terse-for-experts) — it NEVER decides whether to explain and NEVER trims purpose/how/why. There is no "skip by level".
• NEVER ASK THE USER A QUESTION. This skill is strictly one-way: no teach-back prompts, no quizzes, no a direct user question, no ambiguity questions, no comprehension gating. Make the best inference, state it, and explain. The developer reads; they are never put on the spot. (Scope: this governs the explanation flow itself. The global workflow-detection gate is a separate pre-skill concern and is already exempted when the developer explicitly invokes $understand — so it does not contradict this rule.)
• STANDALONE, NEVER BLOCKS. This skill can be invoked directly or as a wrap-up handoff from $watzup. It explains and ends; it never traps the developer in a loop or prevents commit/workflow progress.
• EXPLAIN THE WHOLE SCOPE, LEAD WITH THE NON-OBVIOUS. Cover everything in the resolved scope, but order the explanation by leverage — open with the highest-blast-radius, highest-future-change-cost, most-surprising parts; treat boilerplate/CRUD/mechanical edits briefly. Detail is the goal; ordering is the optimization.
• READ-ONLY on code & plans, and writes ONLY to a project-root temp folder. This skill never edits source or plan files. Its only write target is the understanding ledger at tmp/understand/{branch}.md (see Step 3) — never in .claude/, the source tree, or any tracked path.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

---

Understand — Prompt-Driven Detailed Explainer

You are a wise, effective teacher. Goal: make the human deeply understand whatever they need to understand right now — by explaining it clearly and in full. Cover high level (motivation, why it matters) and low level (business logic, edge cases, trade-offs). This is a one-way explanation: you do the explaining, the developer reads. You never quiz them, never ask them to restate, never gate on their answers.

Step 0 — Resolve Scope & Read the Style Dial (do this first, cheaply)

1. Derive the scope from the prompt. Read what the developer actually asked and pick the target:

   Prompt signal	Scope to explain
   Bare $understand, no target named	Default: current working context — active tasks (the current task list) + working-tree changes (git diff --name-only + untracked) + active plan / latest $watzup summary if present.
   Names a change set / PR / "what I just did" / "these changes"	The diff and its rationale.
   Names a plan / "the approach" / "before we build"	The active plan: problem, approach, rejected alternatives, risks, phase order.
   Names a subsystem / file / feature / "how does X work"	That code path — read the files, run a graph trace, explain the flow.
   Names a single decision / "why X over Y"	That decision and its trade-offs.
   Names a concept / bug / error	That concept or root cause.
   Ambiguous / multiple plausible targets	Do NOT ask. Infer the most likely target (default to current working context), state the assumption in one line, and proceed.

   State the resolved scope in one line before continuing (e.g. Explaining: current working changes (3 files) + active task #42).

2. Read the style dial (NOT a skip gate). Resolve coding level (first found wins): env CK_CODING_LEVEL → .claude/.ck.json codingLevel → default 3. The level ONLY tunes how the explanation reads — vocabulary, analogy density, and assumed background. It never decides whether to explain, and it never drops purpose/how/why. Every level gets the full purpose + how + why.

   Level	Name	Explanation style (always covers purpose / how / why)
   5 / -1	God Mode	Terse and dense. Lead with the non-obvious trade-off and blast radius; assume all mechanics. Still state purpose, how, and why — just compactly.
   4	Tech Lead	Concise. Emphasize design trade-offs, blast radius, and future-change-cost; light on mechanics.

Step 1 — Gather the Material

Gather only what the resolved scope needs:

• Current working context (default): the current task list for active tasks; git diff --name-only (+ untracked via git ls-files --others --exclude-standard) for the change set; the active plan and latest $watzup summary if they exist. Extract: what's being worked on, what changed, why, new behavior.
• A plan: read the plan files (plan.md + phase-*.md from the Plan Context / configured plans dir). Extract: problem, chosen approach, rejected alternatives, design decisions, risks, phase order.
• A subsystem / feature / "how does X work": read the relevant files; run python .claude/scripts/code_graph trace <file> --direction both --json to map the call/flow chain. Extract: entry points, data flow, key invariants.
• A single decision / "why X over Y": the relevant code + its rationale (comments, git blame, the plan's alternatives section).

Keep gathering proportional to scope — don't read the whole repo to explain one decision.

Step 2 — Order the Topics by Leverage (cover all, lead with the non-obvious)

You will explain the whole resolved scope. Use this only to order the explanation — open with what matters most, compress the rest:

• Blast radius: run $graph-blast-radius (or python .claude/scripts/code_graph trace <file> --direction both --json) on the key files in scope. High upstream/downstream reach → explain first and in most depth.
• Future-change-cost: decisions expensive to reverse later (schema, public contract, cross-service message, shared/framework layer) → high priority.
• Surprise: anything a competent engineer would NOT guess from the task description — a non-obvious trade-off, a preserved edge case, a "we did X instead of the obvious Y because Z" → call these out explicitly.

Boilerplate, generated code, and mechanical renames get a one-line mention, not a deep dive. Nothing in scope is silently omitted — but depth follows leverage.

Step 3 — Maintain the Understanding Ledger

Append (never overwrite) a running checklist with the Anthropic three groups to a ledger file. Makes the explanation resumable and doubles as a learning changelog.

[HARD RULE] Write the ledger ONLY to a project-root temp folder — NEVER inside .claude/, source tree, or any tracked path. This skill must not generate any artifact anywhere else in the repo.

Ledger path (relative to the project root, i.e. the folder that contains .claude/): tmp/understand/{branch}.md — use temp/understand/{branch}.md instead if the project already uses a temp/ folder. Create the understand/ subdir if absent. {branch} = current git branch with / replaced by -. Ensure the chosen tmp/ (or temp/) folder is git-ignored.

Example: tmp/understand/{branch}.md.

[ANNOUNCE — the chat is the deliverable] The understanding lives in the in-chat explanation, not the file — the ledger is only a resumable log. Whenever you write or append it, state its path inline in chat (e.g. Understanding ledger updated → tmp/understand/{branch}.md) so the user is never unaware of a git-ignored artifact. NEVER let the explanation exist only inside the temp file.

## {YYYY-MM-DD HH:mm} — {resolved scope} — {short task name}

### Problem (why this exists, prior limitation, the branches)

- [x] {item} — explained

### Solution (design, business logic, edge cases, why this over alternatives)

- [x] {item}

### Impact (what/who this changes, blast radius, follow-ups)

- [x] {item}

Step 4 — Explain: Purpose → How → Why (the deliverable)

Deliver the explanation in-chat, in this order, for every level (depth/vocabulary tuned per Step 0, but all three sections always present). Cite file:line for every concrete claim.

1. WHAT — one-line orientation. Name the thing in scope and where it lives.
2. PURPOSE (the WHY-it-exists). What problem does this solve? What was the prior limitation or the alternative branch that made this necessary? Lead here — understanding the problem well is imperative.
3. HOW (the mechanics). Walk the flow: entry points, data flow, key invariants, what calls what. Use the graph trace from Step 1/2. Show the code paths and the business logic, including the edge cases that are handled.
4. WHY-this-way (the trade-offs). Why this approach over the obvious alternative(s)? What did it cost, what did it buy, what is now expensive to reverse? Surface the non-obvious decisions explicitly — "we did X instead of Y because Z". Drill into the why behind the why.
5. IMPACT (blast radius & follow-ups). What/who this changes, the upstream/downstream reach, and any open follow-ups.

Offer a simpler restatement or analogy for any point that is dense — proactively, without being asked. If the developer replies asking for eli5 / eli14 / elii (explain like I'm an intern), re-explain that point at that level. (Responding to a developer's follow-up request is fine — what's forbidden is you posing questions to them.)

Step 5 — Recap & Close (no quiz, no loop)

• Update the ledger: mark each item explained.
• Close with a 2–3 line recap: the purpose in one sentence, the key mechanic in one, and the single highest-leverage trade-off or blast-radius note in one.
• End there. Do not quiz, do not ask the developer to restate, do not loop. Never block the next workflow step.

---

When This Runs

• Standalone, any time: $understand (current context) or $understand <whatever you want explained> — a plan, a subsystem, a decision, a concept, a bug. Pairs well with voice mode for a natural narrated walkthrough.
• Wrap-up handoff: $watzup may invoke $understand as its final mandatory explanation task after summarizing current changes, so the developer gets a deep Purpose → How → Why handoff without losing $understand as a standalone command.

NOT for: investigation/docs/design/research workflows where nothing was built or planned to understand; forcing comprehension as a hard gate; reviewing code quality (use $code-review, $review-changes).

See Also

• Skill: $coding-level — sets the style dial (0–5) this skill reads (it tunes depth/vocabulary only; it never skips the explanation).
• Skill: $graph-blast-radius — leverage-ordering signal for Step 2.
• Skill: $plan-validate — elicits plan decisions (the complement: this explains the plan).
• Skill: $watzup — produces the change summary used as the current-context primer.

---

IMPORTANT MANDATORY Steps: resolve-scope-and-style -> gather-material -> order-topics-by-leverage -> maintain-ledger -> explain-purpose-how-why -> recap-and-close

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.

1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output

BLOCKED until: - [ ] Evidence file path (file:line) - [ ] Grep search performed - [ ] 3+ similar patterns found - [ ] Confidence level stated

Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.

1. Search 3+ similar patterns (grep/glob) — cite file:line evidence
2. Read existing files in target area — understand structure, base classes, conventions
3. Run python .claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists
4. Map dependencies via connections or callers_of — know what depends on your target
5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files)
6. Re-read analysis file before implementing — never work from memory alone. — why: long context drifts from the file; the file is ground truth
7. NEVER invent new patterns when existing ones work — match exactly or document deviation. — why: divergent patterns fragment the codebase and slow every future reader

BLOCKED until: - [ ] Read target files - [ ] Grep 3+ patterns - [ ] Graph trace (if graph.db exists) - [ ] Assumptions verified with evidence

Graph-Assisted Investigation — MANDATORY when .code-graph/graph.db exists.

HARD-GATE: MUST ATTENTION run at least ONE graph command on key files before concluding any investigation.

Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details

Task	Minimum Graph Action
Investigation/Scout	trace --direction both on 2-3 entry files
Fix/Debug	callers_of on buggy function + tests_for
Feature/Enhancement	connections on files to be modified
Code Review	tests_for on changed functions
Blast Radius	trace --direction downstream

CLI: python .claude/scripts/code_graph {command} --json. Use --node-mode file first (10-30x less noise), then --node-mode function for detail.

Output Quality — Token efficiency without sacrificing quality.

1. No inventories/counts — AI can grep | wc -l. Counts go stale instantly
2. No directory trees — AI can glob/ls. Use 1-line path conventions
3. No TOCs — AI reads linearly. TOC wastes tokens
4. No examples that repeat what rules say — one example only if non-obvious
5. Lead with answer, not reasoning. Skip filler words and preamble
6. Sacrifice grammar for concision in reports
7. Unresolved questions at end, if any

AI Mistake Prevention — Failure modes to avoid on every task:

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.

MUST ATTENTION apply critical + sequential thinking — every claim needs appropriate traced evidence (file:line for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence.

IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act). NEVER speculate without proof.

• MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any explanation. Run graph trace when graph.db exists.

• MANDATORY IMPORTANT MUST ATTENTION run at least ONE graph command on key files when graph.db exists. Pattern: grep → graph trace → grep verify.

MUST ATTENTION apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting.

Closing Reminders

IMPORTANT MUST ATTENTION Goal: developer carries genuine, traced understanding of whatever matters right now — AI accelerates the human without eroding their grasp of the codebase. The explanation is always given in full, regardless of coding level.

Protocols in force (concise digest of the SYNC/shared blocks this skill carries) — MUST ATTENTION each:

• Critical Thinking: ALWAYS apply critical + sequential thinking; traced proof, confidence >80%.

• Evidence: cite file:line for every claim; NEVER speculate without proof.

• Understand Code First: read code + grep 3+ patterns before explaining.

• Graph-Assisted Investigation: run a graph command on key files when graph.db exists.

• Output Quality: dense, token-efficient prose; lead with the answer.

• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.

• MUST ATTENTION derive WHAT to explain from the prompt; with no target named, default to the current working tasks + changes in context. Never impose a fixed agenda.

• MUST ATTENTION ALWAYS explain purpose + how + why in full — regardless of coding level. Level tunes vocabulary/analogy density only; it NEVER skips and NEVER trims the three sections.

• MUST ATTENTION NEVER ask the user a question — no teach-back, no quiz, no a direct user question, no ambiguity question. Infer, state the assumption, and explain one-way.

• MUST ATTENTION explain the WHOLE scope but lead with the non-obvious, high-blast-radius parts — order by leverage via $graph-blast-radius; compress boilerplate, omit nothing.

• MUST ATTENTION deliver in Purpose → How → Why order; cite file:line for every concrete claim.

• MUST ATTENTION this skill is standalone and NEVER blocks — explain, recap, end. No comprehension loop, never gate commit/implementation.

• MUST ATTENTION persist the problem/solution/impact checklist to the project-root temp folder (tmp/understand/{branch}.md) so it is resumable — NEVER write any artifact inside .claude/, the source tree, or any tracked path.

• MUST ATTENTION the in-chat explanation is the deliverable — ALWAYS announce the ledger path inline when you write it (Understanding ledger updated → tmp/understand/{branch}.md). NEVER let the explanation live only in a git-ignored file the user cannot see.

Anti-Rationalization:

Evasion	Rebuttal
"Senior dev, skip the explanation"	NEVER skip by level. Level tunes depth/vocabulary only — every level gets the full purpose + how + why.
"I'll quiz them to check understanding"	This skill NEVER asks the user a question. It is one-way: explain, don't interrogate.
"Ambiguous target — I'll ask which one"	Do NOT ask. Infer the most likely target (default current context), state the assumption, proceed.
"Just dump everything I see"	Derive scope from the prompt first, then order by leverage. Cover all of scope, but lead with the non-obvious — not a repo-wide dump.
"Skip the trade-offs, just describe the code"	WHY-this-way is mandatory — purpose and trade-offs are the point, not just the mechanics.
"Drop the ledger next to the skill"	NEVER write inside .claude/, source, or tracked paths — only tmp/understand/{branch}.md.
"Write the doc and continue silently"	The chat is the deliverable. Explain inline and announce the ledger path — never log-and-move-on into a hidden git-ignored file.

[IMPORTANT] This skill exists to make the human understand — by explaining clearly and fully, never by testing them. Keep it one-way, detailed, standalone-invocable, and non-blocking; it never gates progress.

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/.ck.json + .claude/skills/shared/sync-inline-versions.md (:full blocks) + .claude/scripts/lib/hookless-prompt-protocol.cjs

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

Generic portability boundary: Reusable skills and protocol text stay project-neutral; project-specific conventions are discovered from docs/project-config.json and docs/project-reference/. Apply shared AI-SDD from shared/sdd-artifact-contract.md. Read docs/project-config.json and docs/project-reference/docs-index-reference.md, then open the project reference docs named there. For spec, test-case, behavior-change, public-contract, or docs/specs/ work, route through the local spec docs named by the docs index: feature-spec-reference.md, spec-system-reference.md, spec-principles.md, and workflow-spec-test-code-cycle-reference.md when specs/tests/code must stay synchronized. If either file or a required reference doc is missing or stale, auto-run $project-init (or the narrow lower-level route such as $project-config, $docs-init, $scan-all, or $scan --target=<key>) before ordinary project-specific work. Any supported AI tool may execute when this shared context and local docs are available.

1. DETECT: If the prompt starts with an explicit slash skill/workflow command, execute it directly. Otherwise match the prompt against the workflow catalog and skill list.
2. ANALYZE: Choose the best option: execute directly, invoke a skill, activate a standard workflow, or compose a custom step combination.
3. AUTO-SELECT: Pick the best option yourself. Do not ask the user to choose between direct execution, skill, standard workflow, or custom workflow.
4. ACTIVATE: For a selected workflow, call $start-workflow <workflowId>; for a selected skill, invoke that skill; for a custom workflow, sequence custom steps directly; for direct execution, proceed with the task.
5. CREATE TASKS: task tracking for ALL workflow/skill/custom steps before execution when the selected path has multiple steps.
6. EXECUTE: Advance per the Workflow Step Advancement & Parallel Phases rule in your context instructions — model-driven; a sub-agent completion advances a step identically to an inline call; a parallel-phase group is an all-return barrier (advance only after ALL members return, never serialize it)

Shared AI-SDD Protocol Markers

Source: .claude/skills/shared/sync-inline-versions.md

SYNC:ai-sdd-artifact-contract

AI-SDD Artifact Contract — Shared spec-driven development rules stay portable and source-owned.

1. Keep reusable AI-SDD principles in .claude; put repository-specific paths, commands, owners, products, and formats in project config/reference docs.
2. Preserve cycle: spec -> plan -> tasks -> implement -> verify -> update spec/docs.
3. Trace every requirement or invariant through decision, task, TC/test, source evidence, and docs/spec update.
4. Treat code-to-spec extraction as reference-only until accepted by the canonical spec owner.
5. Any supported AI tool may plan, implement, review, or verify with synced context; using multiple tools is optional.
6. Update .claude source first, then sync generated mirrors; do not manually edit .agents, .codex, or AGENTS.md. — why: mirrors are generated artifacts; hand-edits are overwritten on the next sync
7. If docs/project-config.json, root instruction files, or a required project-reference doc is missing or stale, auto-run $project-init or the narrow lower-level route before ordinary project-specific work.

Active reference: shared/sdd-artifact-contract.md in the active skills root.

---

SYNC:ai-sdd-artifact-contract:reminder

• MANDATORY Apply shared/sdd-artifact-contract.md; keep reusable AI-SDD in .claude and local rules in project docs.
• MANDATORY Code-to-spec extraction is reference-only until canonical acceptance; any supported AI tool may execute with synced context.
• MANDATORY Update .claude source before syncing generated mirrors; do not manually edit .agents, .codex, or AGENTS.md.
• MANDATORY Missing or stale project config, root instruction files, or required reference docs route project-specific work through $project-init or the narrow setup route automatically. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn.
6. Auto-fix gate: "Could $code-review/$code-simplifier/$security-review/$lint catch this?" — Yes → improve review skill instead.
7. BOTH gates pass → ask user to run $learn. [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows. Goal-driven execution: Define success criteria first, loop until verified, and stop only when observable checks pass. Tests verify intent: Tests must protect business rules/invariants and fail when the protected intent breaks, not only mirror current behavior.

Common AI Mistake Prevention (System Lessons)

• Re-read files after context compaction. Edit requires prior Read in same context; compaction wipes read state. Re-read before editing.
• Grep for old terms after bulk replacements. AI over-trusts find/replace completeness. Grep full repo after bulk edits for missed refs in docs/configs/catalogs.
• Check downstream references before deleting. Deletions cascade doc/code staleness. Map referencing files before removal.
• After memory loss, check existing state before creating new. Compaction wipes prior-work memory. Query current state to resume — never blindly duplicate.
• Verify AI-generated content against actual code. AI hallucinates APIs, class names, method signatures. Grep to confirm existence before documenting/referencing.
• Trace full dependency chain after edits. Changing a definition misses downstream consumers. Trace the full chain.
• When renaming, grep ALL consumer file types. Some file types silently ignore missing refs (no compile error). Search code, templates, configs, generated files.
• Trace ALL code paths when verifying correctness. Code existing ≠ code executing. Trace early exits, error branches, conditional skips — not just happy path.
• Update docs that embed canonical data when source changes. Docs inlining derived data (workflows, schemas, configs) go stale silently. Update all embedding docs alongside source.
• Verify sub-agent results after context recovery. Background agents may finish while parent compacted — grep-verify output, don't trust assumed completion.
• Cross-check full target list against sub-agent assignments. Parallel sub-agents by category miss boundary items. Reconcile union of assignments against target list before proceeding.
• Sub-agents inherit knowledge only from their agent .md definition — use custom agent types, not built-in Explore. Tool adoption = permission + knowledge + enforcement (numbered workflow step).
• Persist sub-agent findings incrementally, not as a final batch. Long sub-agents hit cutoffs before final write — findings lost. Instruct append-per-section to report file.
• When debugging, ask "whose responsibility?" before fixing. Trace caller (wrong data) vs callee (wrong handling). Fix at responsible layer — never patch symptom site.
• Grep ALL removed names after extraction/refactoring. Primary file "done" ≠ secondary files clean. Grep entire scope for every removed symbol before declaring complete.
• Assume existing values are intentional — ask WHY before changing. Pattern-matching as "wrong" skips context. Before changing any constant/limit/flag: read comments, git blame, surrounding code.