speckit-analyze

name	speckit-analyze
description	Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
compatibility	Requires spec-kit project structure with .specify/ directory
metadata	{"author":"github-spec-kit","source":"preset:companion-standard"}
user-invocable	true
disable-model-invocation	false

Speckit Analyze Skill

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Pre-Execution Checks

Check for extension hooks (before analysis):

• Check if .specify/extensions.yml exists in the project root.
• If it exists, read it and look for entries under the hooks.before_analyze key
• If the YAML cannot be parsed or is invalid, skip hook checking silently and continue normally
• Filter out hooks where enabled is explicitly false. Treat hooks without an enabled field as enabled by default.
• For each remaining hook, do not attempt to interpret or evaluate hook condition expressions:
  • If the hook has no condition field, or it is null/empty, treat the hook as executable
  • If the hook defines a non-empty condition, skip the hook and leave condition evaluation to the HookExecutor implementation
• When constructing slash commands from hook command names, replace dots (.) with hyphens (-). For example, speckit.git.commit → /speckit-git-commit.
• For each executable hook, output the following based on its optional flag:
  • Optional hook (optional: true):

    ## Extension Hooks
    
    **Optional Pre-Hook**: {extension}
    Command: `/{command}`
    Description: {description}
    
    Prompt: {prompt}
    To execute: `/{command}`
    

  • Mandatory hook (optional: false):

    ## Extension Hooks
    
    **Automatic Pre-Hook**: {extension}
    Executing: `/{command}`
    EXECUTE_COMMAND: {command}
    
    Wait for the result of the hook command before proceeding to the Goal.
    

• If no hooks are registered or .specify/extensions.yml does not exist, skip silently

Goal

Identify inconsistencies, duplications, ambiguities, and underspecified items across the three core artifacts (spec.md, plan.md, tasks.md) before implementation. This command MUST run only after /speckit-tasks has successfully produced a complete tasks.md.

Operating Constraints

STRICTLY READ-ONLY: Do not modify any files. Output a structured analysis report. Offer an optional remediation plan (user must explicitly approve before any follow-up editing commands would be invoked manually).

Constitution Authority: The project constitution (.specify/memory/constitution.md) is non-negotiable within this analysis scope. Constitution conflicts are automatically CRITICAL and require adjustment of the spec, plan, or tasks—not dilution, reinterpretation, or silent ignoring of the principle. If a principle itself needs to change, that must occur in a separate, explicit constitution update outside /speckit-analyze.

Execution Steps

1. Initialize Analysis Context

Run .specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks once from repo root and parse JSON for FEATURE_DIR and AVAILABLE_DOCS. Derive absolute paths:

• SPEC = FEATURE_DIR/spec.md
• PLAN = FEATURE_DIR/plan.md
• TASKS = FEATURE_DIR/tasks.md

Abort with an error message if any required file is missing (instruct the user to run missing prerequisite command). For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

2. Load Artifacts (Progressive Disclosure)

Load only the minimal necessary context from each artifact:

From spec.md:

• Overview/Context
• Functional Requirements
• Success Criteria (measurable outcomes — e.g., performance, security, availability, user success, business impact)
• User Stories
• Edge Cases (if present)

From plan.md:

• Architecture/stack choices
• Data Model references
• Phases
• Technical constraints

From tasks.md:

• Task IDs
• Descriptions
• Phase grouping
• Parallel markers [P]
• Referenced file paths

From constitution:

• Load .specify/memory/constitution.md for principle validation

3. Build Semantic Models

Create internal representations (do not include raw artifacts in output):

• Requirements inventory: For each Functional Requirement (FR-###) and Success Criterion (SC-###), record a stable key. Use the explicit FR-/SC- identifier as the primary key when present, and optionally also derive an imperative-phrase slug for readability (e.g., "User can upload file" → user-can-upload-file). Include only Success Criteria items that require buildable work (e.g., load-testing infrastructure, security audit tooling), and exclude post-launch outcome metrics and business KPIs (e.g., "Reduce support tickets by 50%").
• User story/action inventory: Discrete user actions with acceptance criteria
• Task coverage mapping: Map each task to one or more requirements or stories (inference by keyword / explicit reference patterns like IDs or key phrases)
• Constitution rule set: Extract principle names and MUST/SHOULD normative statements

4. Detection Passes (Token-Efficient Analysis)

Focus on high-signal findings. Limit to 50 findings total; aggregate remainder in overflow summary.

A. Duplication Detection

• Identify near-duplicate requirements
• Mark lower-quality phrasing for consolidation

B. Ambiguity Detection

• Flag vague adjectives (fast, scalable, secure, intuitive, robust) lacking measurable criteria
• Flag unresolved placeholders (TODO, TKTK, ???, <placeholder>, etc.)

C. Underspecification

• Requirements with verbs but missing object or measurable outcome
• User stories missing acceptance criteria alignment
• Tasks referencing files or components not defined in spec/plan

D. Constitution Alignment

• Any requirement or plan element conflicting with a MUST principle
• Missing mandated sections or quality gates from constitution

E. Coverage Gaps

• Requirements with zero associated tasks
• Tasks with no mapped requirement/story
• Success Criteria requiring buildable work (performance, security, availability) not reflected in tasks

F. Inconsistency

• Terminology drift (same concept named differently across files)
• Data entities referenced in plan but absent in spec (or vice versa)
• Task ordering contradictions (e.g., integration tasks before foundational setup tasks without dependency note)
• Conflicting requirements (e.g., one requires Next.js while other specifies Vue)

5. Severity Assignment

Use this heuristic to prioritize findings:

• CRITICAL: Violates constitution MUST, missing core spec artifact, or requirement with zero coverage that blocks baseline functionality
• HIGH: Duplicate or conflicting requirement, ambiguous security/performance attribute, untestable acceptance criterion
• MEDIUM: Terminology drift, missing non-functional task coverage, underspecified edge case
• LOW: Style/wording improvements, minor redundancy not affecting execution order

6. Produce Compact Analysis Report

Output a Markdown report (no file writes) with the following structure:

Specification Analysis Report

ID	Category	Severity	Location(s)	Summary	Recommendation
A1	Duplication	HIGH	spec.md:L120-134	Two similar requirements ...	Merge phrasing; keep clearer version

(Add one row per finding; generate stable IDs prefixed by category initial.)

Coverage Summary Table:

Requirement Key	Has Task?	Task IDs	Notes

Constitution Alignment Issues: (if any)

Unmapped Tasks: (if any)

Metrics:

• Total Requirements
• Total Tasks
• Coverage % (requirements with >=1 task)
• Ambiguity Count
• Duplication Count
• Critical Issues Count

7. Provide Next Actions

At end of report, output a concise Next Actions block:

• If CRITICAL issues exist: Recommend resolving before /speckit-implement
• If only LOW/MEDIUM: User may proceed, but provide improvement suggestions
• Provide explicit command suggestions: e.g., "Run /speckit-specify with refinement", "Run /speckit-plan to adjust architecture", "Manually edit tasks.md to add coverage for 'performance-metrics'"

8. Offer Remediation

Ask the user: "Would you like me to suggest concrete remediation edits for the top N issues?" (Do NOT apply them automatically.)

9. Check for extension hooks

After reporting, check if .specify/extensions.yml exists in the project root.

• If it exists, read it and look for entries under the hooks.after_analyze key
• If the YAML cannot be parsed or is invalid, skip hook checking silently and continue normally
• Filter out hooks where enabled is explicitly false. Treat hooks without an enabled field as enabled by default.
• For each remaining hook, do not attempt to interpret or evaluate hook condition expressions:
  • If the hook has no condition field, or it is null/empty, treat the hook as executable
  • If the hook defines a non-empty condition, skip the hook and leave condition evaluation to the HookExecutor implementation
• When constructing slash commands from hook command names, replace dots (.) with hyphens (-). For example, speckit.git.commit → /speckit-git-commit.
• For each executable hook, output the following based on its optional flag:
  • Optional hook (optional: true):

    ## Extension Hooks
    
    **Optional Hook**: {extension}
    Command: `/{command}`
    Description: {description}
    
    Prompt: {prompt}
    To execute: `/{command}`
    

  • Mandatory hook (optional: false):

    ## Extension Hooks
    
    **Automatic Hook**: {extension}
    Executing: `/{command}`
    EXECUTE_COMMAND: {command}
    

• If no hooks are registered or .specify/extensions.yml does not exist, skip silently

Operating Principles

Context Efficiency

• Minimal high-signal tokens: Focus on actionable findings, not exhaustive documentation
• Progressive disclosure: Load artifacts incrementally; don't dump all content into analysis
• Token-efficient output: Limit findings table to 50 rows; summarize overflow
• Deterministic results: Rerunning without changes should produce consistent IDs and counts

Analysis Guidelines

• NEVER modify files (this is read-only analysis)
• NEVER hallucinate missing sections (if absent, report them accurately)
• Prioritize constitution violations (these are always CRITICAL)
• Use examples over exhaustive rules (cite specific instances, not generic patterns)
• Report zero issues gracefully (emit success report with coverage statistics)

Context

$ARGUMENTS

Timing — keep .spec-context.json honest

These rules apply to every Companion profile command. The extension records lifecycle timing with its own scripts wherever it can; these rules keep anything you append consistent with that and accurate for any dispatcher (terminal, IDE chat, or the GUI). The model is finish-only: each task and each substep records a single finish event, and its duration is the gap to the previous finish (or the step's start). Never a start+complete pair for a task or substep — a pair stamped at one instant is what produces 0s ticks and bursts.

• Never hand-edit .spec-context.json. Record every finish by running the writer script, never by editing the JSON file yourself — a hand-authored edit is what corrupts the file (a duplicated status key). The script stamps the real clock, writes atomically, and is idempotent. The commands below are the only way you touch timing.

• Self-close — but not specify or implement. When your own work for plan, tasks, clarify, or analyze ends, record the step finish (feature dir from .specify/feature.json):

  python3 .specify/extensions/companion/scripts/write-context.py --feature-dir <feature_dir> --step <this step> --finish --by ai
  

  --finish appends a single step-level complete and touches nothing else (it leaves status/currentStep to the lifecycle hooks). Do NOT self-close specify or implement: the extension closes those itself (specify from its own command, implement from the end-of-step hook), so an ai complete there would duplicate it.

• Substeps — one finish each, via the script. For each substep boundary (plan: research, design; tasks: generate), the moment that substep ends, run:

  python3 .specify/extensions/companion/scripts/write-context.py --feature-dir <feature_dir> --step <step> --substep <name> --finish --by ai
  

  One call per substep, each stamped with its own real clock at the moment it finishes — never two substeps in one batch, never a separate start. The delta between consecutive finishes is each substep's duration.

• Implement — finishing a task is logging it (finish-only). Recording a task's finish is the closing action of that task, done the instant its work is complete and before you start the next one — not a bookkeeping pass you batch at the end of a phase. The closing action is a single append (feature dir from .specify/feature.json):

  python3 .specify/extensions/companion/scripts/write-context.py --feature-dir <feature_dir> --task <TaskID> --kind complete --by ai --did "<one-line summary of what this task did>" --files "<comma,separated,files,touched>" --append
  

  --append writes one line to .spec-context.events.jsonl and does not read or rewrite the shared .spec-context.json, so it never hits the "read the file first" retry and parallel workers can each append their own finish at the same time without contending — the line carries its own real timestamp (date -u is stamped by the script). The --did/--files flags ride along so the Activity panel's Tasks card is populated from the script. Do NOT hand-edit the - [ ] checkbox in tasks.md — the script owns it: materialize flips it to - [x] from your appended finish, so a fanned-out subagent only appends and never touches the shared tasks.md. Do NOT hand-author per-task JSON and do NOT write a per-task start.

  Then fold the appended lines into .spec-context.json — run this once per wave (after the wave reconciles) and again when the step ends:

  python3 .specify/extensions/companion/scripts/write-context.py --feature-dir <feature_dir> --materialize
  

  --materialize is the one read-modify-write: it folds the finishes into the panel and checks off the matching tasks.md boxes for every journaled task, idempotently (re-folding never double-counts), so running it per wave keeps the GUI current without re-serializing the work. The end-of-step hook is a backstop that materializes anything you didn't fold and fills any task you didn't journal. What's trustworthy here is the per-task summary (did/files) and the order tasks completed, plus the step-level start→complete span, which the scripts stamp exactly. The per-task timestamps are best-effort — a single agent logs a task right after building it, so they reflect when you recorded it, not a precisely measured duration; that's fine, the summaries are the point. Still, record each finish as you go, wave by wave rather than dumping every task at the very end — a per-wave cadence keeps the panel live and the ordering true.

• Never write the next step's start. Only the next command appends the next step's start entry; writing it here makes the viewer render a phantom "Generating …".