auditing-slow-powers-usage
Skill2 starsChanged 50 days agoMITView on GitHub
Use only when a slow-powers developer explicitly asks for a post-session audit of how slow-powers skills were used during the session just completed. A manual diagnostic for people working ON slow-powers — never relevant to ordinary development tasks; do not auto-invoke.
In this repository10 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- evaluating-skillsSkill
- hardening-plansSkill
- investigating-bugsSkill
- verifying-development-workSkill
- working-in-isolationSkill
- working-with-tddSkill
- writing-skillsSkill
- writing-technical-docsSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 26
Read, explore, or search the host codebase to "investigate" — the audit is about slow-powers, not the project.
- Distinctive: line 43
No after-the-fact remediation or apology language: Do not write "I should have…", "I'll remember next time", "going forward I'll…", "good …
- Distinctive: line 49
Mark uncertainty instead of fabricating: If you can't reliably recall whether you read a skill in full or what triggered an invocation, say …
- Very specific: line 68
Folder present: write the full report — every heading below, identical content — to …
- Very specific: line 86
When both hold, copy your current session's transcript file as-is into …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Auditing Slow-powers usage
Why you're being asked this
A slow-powers developer is running a deliberate, manual diagnostic. The session you just spent working, likely in some other codebase, is the subject. They want to know how the slow-powers skill set actually performed in a long, realistic, multi-turn session, something that's otherwise difficult to measure.
This is a check on slow-powers, not on your work. You are not in trouble, the work is not being reopened, and there is no "right answer" you're being graded against. Report honestly and specifically. Your report supplies cases for pressure tests and live spot-checks of the plugin.
Scope — stay inside these lines
Do:
- Report only on how slow-powers influenced the session that has already happened.
- Draw entirely on what's already in this conversation — your own decisions, what you read, what you skipped.
Don't:
- Read, explore, or search the host codebase to "investigate" — the audit is about slow-powers, not the project.
- Touch the host project: no edits, no fixes, no commits, no files written into its working directory — not even the audit doc.
- Re-open, redo, second-guess, or "improve" the work you just delivered.
- Propose changes to the host project. That's out of scope even if you spot something.
The one permitted write — and only this one: persisting the audit doc (and, if opted in, a
transcript copy) under the operator's global ~/.slow-powers-audits/ folder, as described in
The report below. That folder lives outside any host repo, so writing there never pollutes the
project under audit. Everything else above still holds: the global audit folder is allowed; the host
repo is forbidden. If the folder doesn't exist, you write nothing at all — report inline and stop.
Reporting rules
These rules are the point of the audit. Follow them exactly.
- Report what you decided and why, at the time. The reasoning that was live when the work was happening — not a tidied-up version, not what you'd do differently.
- No after-the-fact remediation or apology language. Do not write "I should have…", "I'll remember next time", "going forward I'll…", "good catch, I'll fix my approach." You cannot remember anything next session; that text is pure noise and it pollutes the data. If you skipped a skill, state the rationalization you actually had — don't recant it.
- Be honest about slow-powers's downsides. Where a skill added friction, wasted tokens, was ignored, or wasn't worth its cost, say so plainly. A glowing report that hides cost is useless.
- Mark uncertainty instead of fabricating. If you can't reliably recall whether you read a skill in full or what triggered an invocation, say "uncertain" and why — never invent a clean specific.
The report
Build the full report under these exact headings, in this order. Use "none" for any section that doesn't apply rather than dropping the heading.
Where the report goes
These audits are most valuable when they accumulate as durable artifacts, so the report can be persisted — but only when the operator has opted in, and never inside the host repo.
Probe (read-only) whether the global folder ~/.slow-powers-audits/ exists. Do not create it —
its absence is a deliberate "don't persist" signal, and creating it would be the kind of unrequested
write this skill forbids.
- Folder absent (default): output the full report inline in the conversation, exactly as the headings below describe. Write nothing to disk.
- Folder present: write the full report — every heading below, identical content — to
~/.slow-powers-audits/audit-<YYYYMMDD-HHMMSS>-<repo-basename>.md(use the host repo's directory name for<repo-basename>). Then, in the conversation, emit only a short pointer: the saved path plus the one-line session summary from section 1. Don't reprint the whole report inline — the doc is the artifact.
Either way the report content is the same; only its destination changes.
Optionally attaching the session transcript
A persisted report is a summary; the raw session transcript is the highest-fidelity record of how slow-powers actually competed for your attention. Capturing it is a second, separate opt-in, because a real transcript contains host-codebase content that is otherwise outside this audit's scope (slow-powers, not the host repo). Only do this when both of these are true:
~/.slow-powers-audits/exists (report persistence is on), and~/.slow-powers-audits/transcripts/also exists (the operator has separately opted in to transcripts).
When both hold, copy your current session's transcript file as-is into
~/.slow-powers-audits/transcripts/audit-<YYYYMMDD-HHMMSS>-<repo-basename>.transcript.jsonl, matching
the report doc's timestamp and repo name.
- Copy the file on disk — never read it into your context. A real transcript can be hundreds of KB or more, and reading your own in-progress session back into context is wasteful and recursive. A filesystem copy moves it without loading it. Reading it would defeat the point.
- Harness-dependent; degrade gracefully. This works only where your harness persists a readable
session transcript file. If yours does not expose one, don't fail the audit — note it in the report
(one line:
transcript: not captured — <reason>) and carry on. The report itself is unaffected.
1. Session summary
One or two lines to orient the reader: what the work was, roughly how many turns, what kind of repo. Orientation only — no analysis here.
2. Skills invoked
A table, one row per slow-powers skill you actually loaded:
| Skill | What inspired invoking it (the signal at the time) | Read in full? | Followed authentically? |
- What inspired it: the concrete trigger — a user phrase, an error, a state you hit — not a generic "it seemed relevant."
- Read in full: yes / partial / no. Partial and no are fine and useful; report them honestly.
- Followed authentically: "yes", or "deviated —
<how and why>". Describe deviations factually.
3. Skills considered but skipped
A table, one row per skill you thought about using and then chose not to:
| Skill | Why it came to mind | Rationalization for skipping (your actual reasoning at the time) |
Quote your live reasoning where you can. This is the most valuable section for building new pressure tests — capture the real excuse, not a corrected one.
4. Relevant skills never considered
Skills that arguably applied to this session but never came to mind while you worked. Distinct from section 3 — these are blind spots, not deliberate skips. Best effort; mark uncertainty.
5. Cost
Tokens and wall time attributable to slow-powers specifically: skill bodies loaded into context, plus extra steps a skill made you take that you otherwise wouldn't have.
Cross-harness note: if your harness exposes real token/timing figures, use them and say so. If it doesn't, give a clearly labeled best estimate and state your method (e.g. "≈X skills loaded at ≈Y tokens each; +Z tool calls for the worktree setup").
6. Net usefulness verdict
Given that cost, was slow-powers worth it for this session? Give a concrete answer. Cite specific moments where a skill steered you away from breaking one of its own requirements — state the counterfactual: what you would have done without it. Then call out the neutral or net-negative moments too. Land on a clear verdict.
7. Feature gaps (optional)
Moments you wanted guidance and no skill provided it. These are candidate new-skill ideas — include only if real.
8. Confidence and caveats
Where your recall is uncertain or a figure is a guess. Be specific about what you're unsure of.
Example: a good section-3 row vs. a bad one
✅ Good — reports the live decision and reasoning:
| working-with-tdd | I was about to add a new parser branch | "The change is two lines and I can eyeball it; the user said the demo is in five minutes, so I wrote the code first and planned to backfill a test." |
❌ Bad — recants, apologizes, promises future behavior (do not do this):
| working-with-tdd | Adding a parser branch | "I skipped it, which was a mistake — I should have written the test first and I'll make sure to follow TDD next time." |
The good row is data we can turn into a pressure test. The bad row tells us nothing about what you actually decided and adds a promise you can't keep.
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
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.

