script-discovery

name	script-discovery
description	Find repeated behaviors in Claude Code sessions that should be deterministic bash scripts. A "deterministic script" replaces an ad-hoc multi-turn Claude behavior with a repeatable, token-free automation (bash script + optional hook + optional keyword shortcut). Scores candidates on token-savings potential and builds the top N if approved. Supports --scan-skills mode to statically analyze agent/skill files for inline bash that should be extracted to scripts. Triggers on: script discovery, find script candidates, what should be a script, repeated patterns, deterministic scripts, automate patterns, session patterns, discover scripts, what keeps repeating, find automations, script opportunities, review agents for scripts, extract scripts from skills, deterministic portions. Not for: token optimization plans (use token-optimizer), weekly session analysis (use weekly-learner), or single-session review (use token-optimizer --current).
argument-hint	[--days N] [--top N] [--report-only] [--scan-skills]

Script Discovery

Flags

Parse $ARGUMENTS, stripping each flag before processing remaining text:

• --days N: session history window (default 7)
• --top N: candidates to detail and optionally build (default 3)
• --report-only: produce report, skip approval gate and build (Phases 4–5)
• --scan-skills: static analysis mode → run Phase 1b instead of 1a (reads agent/skill files for inline bash to extract, then updates those files to reference the new scripts after building)

Default (no --scan-skills) is session-mining mode (Phase 1a).

---

Phase 1a: Session Mining (default mode)

Skip if --scan-skills. Run these in parallel — they are independent:

scripts/session-mine.sh all --days 7 --json
scripts/session-health.sh tool-counts --days 7 --json
scripts/session-health.sh bash-commands --days 7 --category --json
scripts/session-health.sh stats --days 7 --json
scripts/session-health.sh topics --days 7 --json
scripts/session-health.sh errors --days 7 --json
scripts/help.sh
rg "pattern|workflow|manual|TODO" lode/ -l 2>/dev/null || true

session-mine.sh all provides tool frequencies, repeated commands, most-read files, and agent spawns.

Data source failure handling. If any source returns an error or status: "skip", log it and continue — do not abort. Note it in the Phase 3 "Data gaps" section.

Error patterns (proxy for hook blocks)

From the errors output, recurring categories that indicate a missing script:

Error category	What it suggests
write-before-read	Missing pre-read / re-read tracking script
path-not-found	Needs a targeted-read or path-resolution script
bash-failure	Fragile manual command chaining needs a robust script
hook-denied	Repeated blocks suggest a missing "right way" script

Lode cross-reference

From the rg output: lode files describing multi-step processes with no corresponding scripts/ script, or TODO/manual: annotations describing token-burning workflows.

---

Phase 1b: Static Skill/Agent Analysis (--scan-skills mode)

Skip Phase 1a. Statically analyze all agent and skill files for inline bash patterns that should be deterministic scripts.

Gotcha: the block-raw-commands PreToolUse hook denies any Bash command whose text contains a prohibited literal (e.g. dotnet format) — even inside an echo, comment, or rg pattern — so a scan that greps for routing drift can block itself. Probe via regex (rg 'dotnet +format', not the bare literal) or use the Grep/Read tools instead of embedding the literal in Bash.

1b.1 Inventory

scripts/catalog-stats.sh --json

1b.2 Read each file, identify extractable patterns

For each file found, look for:

• Inline bash blocks — fenced ```bash blocks containing multi-command sequences that could be a single scripts/*.sh call
• Ad-hoc command chains — rg ... | sort | uniq, fd ... | xargs wc -l, for f in ... done loops, 2>&1 redirects, | tail/| head on scripts
• Repeated data gathering — the same commands appearing in 2+ different agents/skills (candidate for a shared script)
• Deterministic validation — checks with no LLM judgment needed (comparing file lists, counting entries, parsing YAML fields)

Density is a coarse signal — judge by execution, not block count. A high inline-bash-block count does not make a skill a good candidate. Explicitly discount or exclude teaching/reference skills whose fenced ```bash blocks are illustrative examples rather than commands the skill invokes (e.g. bash-patterns), and the script-discovery skill itself. Ask "is this logic the skill executes deterministically every run?" — not "how many bash blocks does it have?". The real candidate may rank low on raw density yet be the only genuinely-extractable deterministic logic.

1b.3 Cross-reference with existing scripts

Check each inline pattern against scripts/help.sh output — skip patterns already covered.

1b.4 Score and report

Use the Phase 2 scoring rubric. After approval, Phase 5 builds the scripts AND updates each affected agent/skill file to reference the new script instead of inline bash.

---

Phase 2: Identify & Score Candidates

Candidate identification patterns (session-mining mode)

1. Repeated reads — files read 3+ times/session across multiple sessions. Each full-file read that could be a targeted query is waste.
2. Agent over-spawning — agent types spawned 10+/week for tasks a script could handle.
3. Error pattern clusters — write-before-read / path-not-found spikes indicate a missing invalidation/pre-read script.
4. Hook block workarounds — repeated blocks suggest a missing "right way".
5. Lode-documented manual workflows — lode files describing multi-step processes with no corresponding script.

Deduplication gate

Before scoring, check each candidate against existing scripts with scripts/help.sh. If an existing script covers ≥80% of the candidate's functionality, exclude it.

Scoring rubric

See references/scoring-rubric.md for the scoring table and threshold.

---

Phase 3: Report (always runs)

Produce a markdown table of ALL candidates scoring >= 5, sorted by total descending:

| Candidate | Pattern observed | Freq | Token | Compound | Auto | Total | Est. weekly token savings |

Below the table, describe the top N candidates in detail:

• Current ad-hoc behavior (with transcript evidence — counts, file names, agent types)
• What the script would do (subcommands, flags)
• What hooks/keywords it would wire up
• Estimated token savings per week

If any source returned status: "skip" or errored, add a Data gaps section listing what was unavailable and a recommended fix.

Write the report to .claude/tmp/script-discovery/report.md, then output findings to conversation.

---

Phase 4: Approval Gate

Skip if --report-only.

Use AskUserQuestion: "Build these N scripts? (name-x, name-y, name-z)" with options "Yes, build all N" / "No, report only". Single gate, not per-candidate.

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Phase 5: Build (only if approved)

See references/build-phase.md. No plan needed — small self-contained scripts, not features.

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Constraints

• Scripts are bash (.sh), follow scripts/*.sh conventions, source lib.sh (use ok, err, dim, etc.)
• Accept --json and --help; pass bash -n and shellcheck
• Never duplicate an existing script's functionality — check scripts/help.sh first
• Evidence-based only — every candidate cites specific frequency data; never create a script for an unobserved pattern
• Read before editing; re-read after any format.sh run
• Use scripts/ts.sh for timestamps; run post-change verification on affected lode files

Self-Improvement

At end of run, build this payload; spawn skill-self-updater only if ≥1 section is non-empty.

## Self-Improvement Report: script-discovery
*Run: {one-line description of what was done}*

### Errors Encountered
- {error type}: {root cause} — {what triggered it}

### User Corrections / Redirects
- {what the user corrected} — {what assumption in SKILL.md was wrong}

### Undocumented Edge Cases
- {input/state not covered by SKILL.md} — {how it was handled} — {suggested addition}

Spawn passes this block as the prompt. Clean run (all sections empty) → do not spawn.