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commitment-audit

Checks what you promised against what actually got delivered.
description: "Triggers on prompt mention of 'commitment-audit'."
personal 2 files 10 recent evals

What it does for you

Checks what you promised against what actually got delivered.

What it produces

A recent result, so you can see the kind of work it returns.

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How to get it

These run inside the Snappy workspace. Want this working in your business? I set skills like this up with you, in one focused week.

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For developers how this skill is built, graded, and how it runs

at a glance- the short version

eval modeauto
categoryOps
stages3
dependskrisp, sweep, github

what's inside - the parts that make up a skill 2/4 present

A skill is just a few plain-text files. Only the main one is required. The rest are optional, added as the work needs them. This is what the skill is made of; how it runs is just below.

The skill
state/skills/commitment-audit/SKILL.md present
the skill itself, in plain text
The main file. It says what the skill is and lays out the steps in plain English.
Code
state/lib/commitment-audit.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/commitment-audit/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/commitment-audit/AGENTS.md present
what the AI loads on the fly
Loaded automatically the moment this skill is needed. Kept short on purpose.

how it's graded - what counts as a good run 4 criteria · 2 deterministic · 2 judge

Each row is one thing a good run has to get right. deterministic means a quick check decides, pass or fail. judge means the AI reads the result and rates it. Grading each piece on its own (instead of one overall score) shows exactly where a run fell short, so the fix is obvious.

name
kind
check
output_file_present
deterministic
The file 'state/log/commitment-audit/<date>.md' exists after execution.
output_file_format
judge
The content of 'state/log/commitment-audit/<date>.md' clearly separates 'orphaned', 'silent_shipped', and 'matched' items as specified.
commit_xano_check_performed
judge
The output in 'state/log/commitment-audit/<date>.md' demonstrates an attempt to match commitments against both git commits and Xano rows.
eval_score_correctness
deterministic
The `eval` score reflects `orphaned.length + silent_shipped.length > 0 ? 1.0 : 0.5` based on the content of 'state/log/commitment-audit/<date>.md'.

how it runs - the shared frame every skill uses 3/5 present

Every skill runs the same way. One part does the work, a separate part checks it, and a short loader hands the AI exactly what it needs for the job. Anything this skill doesn't use shows a one-line note saying why, on purpose, not by accident.

makes the work The worker
inferred
load Krisp action-items, from the run command
No worker is named directly, so the command this skill runs is treated as the worker.
checks the work The reviewer
inferred
shape-gate; `score: orphaned from the check command
The check is a quick command that confirms the result looks right.
frame
learns Self-correction
present
fixes itself learns from gaps
When a run hits a gap, the skill gets edited on the spot [FIXED] or queued for a bigger rewrite [LOGGED], so it keeps getting better.
tidies up Background fixes
present
queued for rewrite runs in the background
Bigger fixes that can't be made on the spot get queued and rewritten in the background later.
remembers Run history
present
state/log/evals.ndjson unknown runs
Every run is written down here, so the next time this skill is used it already knows how the last runs went.
Critical rules the things this skill must not get wrong
  1. ALWAYS cache per-repo HEAD hash and skip unchanged repos — git log across 10+ client repos is slow
  2. ALWAYS surface BOTH orphaned (promised, no delivery) AND silent_shipped (delivered, never told the client) — silent ships are as bad as orphans
  3. 0.5 is a valid score when there's nothing to audit — empty output is not a failure
  4. Fuzzy-match is keyword overlap (Jaccard-style), NOT semantic — tune threshold per repo if it under-matches

what it has learned - fixes written back in over time sample

When a run hits something this skill didn't handle, the fix gets written back into the skill so it doesn't happen again. FIXED means it was corrected on the spot. LOGGED means it's queued for a bigger rewrite. Either way, the skill gets a little better and never makes the same mistake twice.

  1. Loading feedback rows…

how the work flows- step by step

inputs krispsweepgithub
1 generator
invoke
load Krisp action-items, parallel git-log across `~/projects/snappy-client-*`, fuzzy-match against commits + Xano timestamps, write `state/log/commitment-audit/<date>.md`
2 auditor
verify
shape-gate; `score: orphaned + silent_shipped > 0 ? 1.0 : 0.5` (0.0 only on shape failure)
3 data
eval log
`state/log/evals.ndjson` (skill: "commitment-audit")

SKILL.md- the skill, written out in plain English

Backed by: state/lib/sweep.ts + state/lib/xano.ts

commitment-audit

Reads ray-todo + sweep snapshot + git log across active client repos. For each open commitment, checks whether a matching commit or Xano row exists. Flags orphans (promised, no delivery) and silent-ships (delivered, never told the client).

Steps

  1. Load open commitments from ~/.claude/cache/krisp/action-items.json.
  2. git log --since="$since" across ~/projects/snappy-client-* repos.
  3. For each commitment, fuzzy-match commit message keywords + Xano

row-created timestamps.

  1. Emit {orphaned, silent_shipped, matched} triage to

state/log/commitment-audit/<date>.md.

Eval

score("commitment-audit", run_id, {
  score: orphaned.length + silent_shipped.length > 0 ? 1.0 : 0.5,
  orphaned: orphaned.length,
  silent_shipped: silent_shipped.length,
  matched: matched.length,
});

0.5 for empty output (valid - nothing to audit). 1.0 when surfaces a real triage item. 0.0 on shape failure.

Gotchas

  • git log across 10+ client repos is slow; cache per-repo HEAD hash and

skip unchanged ones.

  • Fuzzy match is keyword overlap, not semantic - tune threshold per repo.

Rubric

criteria:
  - name: output_file_present
    kind: deterministic
    check: "The file 'state/log/commitment-audit/<date>.md' exists after execution."
  - name: output_file_format
    kind: judge
    check: "The content of 'state/log/commitment-audit/<date>.md' clearly separates 'orphaned', 'silent_shipped', and 'matched' items as specified."
  - name: commit_xano_check_performed
    kind: judge
    check: "The output in 'state/log/commitment-audit/<date>.md' demonstrates an attempt to match commitments against both git commits and Xano rows."
  - name: eval_score_correctness
    kind: deterministic
    check: "The `eval` score reflects `orphaned.length + silent_shipped.length > 0 ? 1.0 : 0.5` based on the content of 'state/log/commitment-audit/<date>.md'."

AGENTS.md- what the AI loads when this skill comes up

commitment-audit - loader

Per-turn rules for the commitment-audit skill. Full reference: state/skills/commitment-audit/SKILL.md. Do not skip these.

Critical Rules

  • ALWAYS cache per-repo HEAD hash and skip unchanged repos - git log across 10+ client repos is slow
  • ALWAYS surface BOTH orphaned (promised, no delivery) AND silent_shipped (delivered, never told the client) - silent ships are as bad as orphans
  • 0.5 is a valid score when there's nothing to audit - empty output is not a failure
  • Fuzzy-match is keyword overlap (Jaccard-style), NOT semantic - tune threshold per repo if it under-matches

Commands

| ui dashboard | state/skills/commitment-audit/resources/ui.openui | |invoke: load Krisp action-items, parallel git-log across ~/projects/snappy-client-*, fuzzy-match against commits + Xano timestamps, write state/log/commitment-audit/<date>.md |verify: shape-gate; score: orphaned + silent_shipped > 0 ? 1.0 : 0.5 (0.0 only on shape failure) |eval log: state/log/evals.ndjson (skill: "commitment-audit")

OpenUI Resource

  • Skill-owned OpenUI Lang resource: state/skills/commitment-audit/resources/ui.openui. Read it before rendering or editing this skill's generated component surface.
  • Treat this resource as a first-class artifact of the skill, not a generic chat response. Improve it when the skill's user-facing output needs to become richer.
  • System resources compose OpenUI primitives and inherit SnappyChat tokens. Use ui_contract: branded in SKILL.md only for deliberate platform or client visuals.

Known Pitfalls

  • Per-repo Jaccard threshold drift - what works for snappy-client-ray may under-match for snappy-client-orbiter. Tune per repo, not globally.
  • Krisp action-items cache lives at ~/.claude/cache/krisp/action-items.json - refresh it via state/bin/krisp/refresh.sh before audit if stale
  • Silent-ship detection is the load-bearing surface - if you're tempted to drop it because output looks redundant, don't (memory: feedback_audit_before_push)

Self-Test

An agent reading this should correctly:

  1. [ ] Skip an unchanged repo via HEAD-hash cache rather than re-running git log
  2. [ ] Score an empty audit at 0.5, not 0.0
  3. [ ] Surface silent-ships even when orphans is empty

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] commitment-audit: <what was missing>" >> state/log/loader-feedback.log

<!-- kernel-ok: historical attribution for the PID-loader pattern. -->

Self-correcting loader (PID feedback)

This is the rule that makes loaders learn. Ported from snappy-kernel, where it demonstrably worked: the snappy-dom-cartographer skill mapped Skool admin UI once, every later ship-agent inherited the full map for free.

Before you finish, do two things:

1. Fix gaps (P - proportional). MANDATORY. If this loader didn't cover your case - if you had to read another file, run an undocumented command, work around a wrong selector, or discover a quirk - you MUST attempt an Edit to this AGENTS.md before you log.

  • Default action: edit this file. Surgical. Add the missing line, table

row, or code example where it belongs. No restructuring.

  • Only LOGGED is allowed when: the fix needs >10 lines, spans multiple

files, or requires a structural rewrite. In that case the state/regen/drain.sh queue picks it up asynchronously.

  • "I didn't have time" / "it's minor" / "the next agent will figure it out"

are NOT valid reasons. Minor gaps compound - that's the whole point of this loop.

  • Concrete example of a valid P-fix: discover agent-browser screenshot

takes path positionally not as --output <path>. One line in a table. Edit it in. Do not just log it.

  • The goal: the next agent never has to leave the loader.

2. Log the result.

echo "[$(date -u +%FT%TZ)] commitment-audit: <what was missing or fixed> [FIXED|LOGGED]" >> state/log/loader-feedback.log
  • FIXED = you patched this loader inline (P-fix).
  • LOGGED = too large for inline; the PostToolUse enqueue + Stop-hook drain

will rewrite the loader from scratch on next session-end.

Do not skip this. Every agent run must leave the system better than it found it. The loader is the setpoint; you are the sensor; the gap is the error signal; closing the gap is the correction.

api.ts- the code it can call

⚠ no api.ts - this skill has no typed action surface

scripts- helper scripts it can run

prose-only skill - 2 inline code blocks live in SKILL.md above (no state/bin/ sidecar yet).

how we check it- the checks, plus the last 10 runs

rubric auto no rubric declared
recent mean 0.98 · 10 runs actor/auditor: unverifiable
deps krisp sweep github
timestamp verb score primary_issue artifact
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -
2026-04-21 15:56Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-16 17:49Z - 0.85 - -
2026-04-16 17:49Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -
2026-04-21 15:56Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -