agentleFS
kkgogogo17kkgogogo17/pi-pstack/skills/show-me-your-work/SKILL.md

show-me-your-work

Skill9 starsChanged 3 months agoMITView on GitHub

Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /skill:show-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.

We split this skill into the rules it gives an agent

4 rules. 2 are common, 1 is distinctive, and 1 is very specific to this project.

  • 2

    Common

    Most of the 58 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    Write each entry the way you'd tell a teammate what you did.

    line 36
  2. Common:

    Prefer evidence produced by committed scripts over hand-made one-offs, so a reviewer can re-run it (the encode-lessons-in-structure …

    line 52
  3. Distinctive:

    Every row maps to a real action.

    line 58
  4. Very specific:

    Read top to bottom, follow the evidence pointers, spot-check.

    line 78

“Common” is measured: kept by at least 6 in 10 of the 58 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Show me your work

For work a human reviews after the fact, a decision trail lets them reconstruct what was decided, why, and on what evidence, without rerunning the work or reading the whole transcript. Keep one canonical log so the trail is consistent and a future agent can find it.

The format

A single TSV file, one row per decision. TSV because GitHub renders it as a sortable table, column -s$'\t' -t and spreadsheets read it, and a row appends with one command. Cells stay single-line. Evidence is a pointer, not prose.

Copy references/decision-log-template.tsv (the header row) to start a clean log. Columns:

  • ts. ISO8601 timestamp. The timeline axis.
  • phase. The phase or workstream.
  • decision. What was chosen or done, one line.
  • why. The reason in plain words. If a principle drove it, say it plainly (explored options first, this was a one-way door), not as a jargon tag.
  • evidence. A link or path that proves it: commit SHA, PR number, file:line, or an artifact, trace, or screenshot path. Never a paragraph.
  • result. The outcome or predicate state: tests green, reverted, pixel-diff 0, INCONCLUSIVE, open.

An example, plain-spoken so a reviewer reads it at a glance. This is illustration only; don't copy these rows into a real log.

ts	phase	decision	why	evidence	result
2026-05-24T09:02:00Z	frame	counted the work first, about 100 components and roughly 75 hours	wanted to know the size before starting a long run	commit 3a9f1c2	found 5 things to sort out before starting
2026-05-24T09:40:00Z	harness	took screenshots of the old version before changing anything	so we can compare old against new and catch any visual change	scripts/snapshot.sh, baseline/	saved 120 reference screenshots
2026-05-24T11:15:00Z	widget	moved the widget styles over without changing how it looks	keep the change small and the result identical	commit 7c21e0a, pixel-diff 0	looks identical, tests pass
2026-05-24T12:30:00Z	widget	threw out a helper's work because its screenshots were blank	checked the real files instead of trusting its summary	worktree reset	reverted, tightened the instructions for next time

Logging a row

Write each entry the way you'd tell a teammate what you did. Plain words, concrete actions, no AI speak or abstract jargon (the unslop skill applies to log text too). A reviewer should understand each row without decoding it.

Use the helper so rows stay well-formed: scripts/log.sh <logfile> <phase> <decision> <why> <evidence> <result>. It stamps ts, writes the header on first use, strips stray tabs/newlines, and prefixes any cell starting with =, +, -, or @ with a single quote so a reviewer opening the log in a spreadsheet doesn't trigger formula execution. A bare printf appending a row works too, but mind those same bytes if cells come from generated or user-supplied text.

Log decision points and checkpoints, not every action: a fork chosen, a unit completed with its verification result, a pivot or revert with its trigger, a blocker surfaced, a gate fixed. For loop runs, one row per iteration. Skip the trivial and self-evident.

Where it lives

By default the log is a working artifact, not committed. Keep it at decisions.tsv in the work dir, or .audit/<task-slug>.tsv when several efforts run at once, and leave it out of git. Most work doesn't need a committed trail; the local log still keeps the run honest and can be discarded after.

Commit it only when the work is ambitious enough that a reviewer needs the trail to trust the result: a large cross-language port, a multi-week migration, anything where confidence has to be shown rather than assumed. A committed log renders as a table in the PR.

Rules

  • One row is one decision or checkpoint. If it doesn't fit on one line, the decision isn't crisp yet.
  • Append-only. A wrong call gets a new row that supersedes it. Never edit or delete history.
  • Prefer evidence produced by committed scripts over hand-made one-offs, so a reviewer can re-run it (the encode-lessons-in-structure principle skill).

Audit the log against the transcript

At the end of the run, before handing back, check the log told the truth. Read $PI_SESSION_FILE for this run. For an earlier same-project session, use pstack_sessions; do not glob Pi's global session directory. Walk the log against what actually happened:

  • Every row maps to a real action. Cut invented or aspirational entries.
  • Each row's evidence resolves and shows what the row claims.
  • A fork, pivot, or abandoned approach that shaped the work but isn't logged is a gap. Add it.
  • Drop padding. If nobody would audit a row, it doesn't earn its place.

Fix the log, not the story. If the work diverged from what a row claims, the row is wrong.

Cross-model review of the trail

Before handing back, you must spawn a subagent on a different model family from the one that did the work. Self-review is not a substitute; the point is fresh eyes you cannot bring yourself. The subagent reads the audit trail and the run's transcript, then flags what the user should pay attention to. Not a redo of the work, a scan for what's suboptimal or risky.

  • Decisions logged with weak or absent evidence.
  • Verification steps skipped or claimed without proof in the transcript.
  • Choices that look risky in hindsight (premature, scope-creeping, papering over a symptom).
  • Gaps the user would otherwise miss on a casual skim.

Every reply for a run that produced a trail ends with an "Attention" section. Lead with the reviewer's model on its own line (reviewed by <model>), then list each flag pointing to specific rows or moments. "No flags" is a valid value; the model name is not. The self-audit asks if the log told the truth; this asks what the user should still scrutinize even when it did.

Reviewing the trail

Read top to bottom, follow the evidence pointers, spot-check. GitHub renders a committed TSV as a table; column -s$'\t' -t decisions.tsv renders it in a terminal. A row whose evidence doesn't resolve, or whose result is unverified, is the audit catching a gap.

Composing this skill

Other skills route their audit trail here instead of inventing one. Reference it by name and let it own the format; don't restate the columns.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.