write-report
Skill2 starsChanged 15 days agoMITView on GitHub
Load before planning or building anything that compares, measures or benchmarks (which is cheaper, faster, better; whether; how much), or when the user says report, write-up, findings or compare. How to offer and run the report-writer agent.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- athina-ai/goose-skillstheir own version, first seen Nov 9, 2026
- adhamhaithameid/write-skillstheir own version, first seen Nov 8, 2026
- gooseworks-ai/goose-skillstheir own version, first seen Nov 1, 2026
- microsoft/healthcareai-examplestheir own version, first seen Oct 13, 2026
- Xia-Ataraxia/craft-skillstheir own version, first seen Jul 3, 2026
- rezendefabio/financas-labtheir own version, first seen May 30, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- athina-ai/goose-skills★ 1.3ksame name
- gooseworks-ai/goose-skills★ 1.3ksame name
- microsoft/healthcareai-examples★ 204same name
- adhamhaithameid/write-skills★ 1same name
- rezendefabio/financas-lab★ 0same name
- Xia-Ataraxia/craft-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository7 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- restore-sessionsSkill
- review-skillSkill
- run-agentSkill
- test-speedupSkill
- weekly-roundupSkill
- write-readmeSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
2
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
- Distinctive: line 28
Run it once the data directory is complete, from the data directory itself:
- Very specific: line 35
Put PLAYWRIGHT_DIR=… in front when a project's notes say the cards need it.
- Distinctive: line 37
Read the reply's last line.
“Common” is measured: kept by at least 6 in 10 of the 5 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.
Files
write-report
The report-writer (claude --agent report-writer) writes the essay a study's data supports: the user's ask quoted
first, one typical unit followed through the numbers, every figure a sourced {key}, a page plus 390 px phone cards,
and a report-checker reading it cold. This skill says how a plan calls for one and how a worker runs it.
Planning
Whenever the work involves data, the planner's round-1 deliverable question offers "report-writer report" as one of its options (beside a page, a table, a script), and a plan that chooses it carries this requirement text, filled in:
- The data directory: where the runs, measurements or logs land, with a
README.mdthat says how each quantity is defined (field names, scorer, units) and nothing written by hand into it afterwards. ASK.mdin that directory: the user's ask verbatim (their own words, with when and where they said it), never the study's question.- The decision question in one sentence: what the report must settle, which arms it compares and by which quantity.
--out <dir>: where the report goes (<data dir>/report/when unsaid).- Checker on:
--no-checkeronly when the user says so. - The acceptance criterion:
check.py --prosePASS on the output, and the user readsreport.htmlat phone width.
Running
Run it once the data directory is complete, from the data directory itself:
cd "<data dir>" && claude -p --agent report-writer ". — <question> --out <dir>"<dir> is absolute or relative to the data directory. Why from there: launched from a project root, the project's
AGENTS.md/CLAUDE.md enters the writer's context, and on 2026-11-06 a base-context report opened on a session that
AGENTS.md described instead of on the data. The writer treats such text as not data, and the data directory has none.
Put PLAYWRIGHT_DIR=… in front when a project's notes say the cards need it.
Read the reply's last line.
- Ends with the output directory, the check.py line and the checker line: the report is written. Open it for the user
at phone width:
"/mnt/c/Program Files/Mozilla Firefox/firefox.exe" -new-window "$(wslpath -w "<dir>/report.html")" &(one window), and record the check.py and checker lines inplans/WORKER_NOTES.md. - Ends with
send-back: needs data: the data cannot settle the ask.<dir>/NEEDS-DATA.mdnames the comparison, the rule that fired (ci_includes_zero,n_below_two,arm_not_run) and a## Collectsection with the arms, how many more runs each and the exact command. Run that command (the study's own, not a stand-in), put the results in the data directory, and rerun the same prompt. Two send-backs on one study are the most the writer makes; on the third run it writes the report and tells the unsettled comparison as unproven. Record each send-back (rule, what was collected, run ids) in WORKER_NOTES. - Ends with
check.py: FAIL, has no check.py line, or endsblocked: <what to run>: the report is not written. Fix the cause the last line names (forblocked:, install or fix what it says, then record it in WORKER_NOTES) and rerun the same prompt. Never record it as done and never editreport.md,numbers.jsonorreport.htmlby hand. - Checker findings:
NOTES.md ## Checkerneeds a row per finding, "fixed" or "rejected:<reason>". An openhighfinding is treated likecheck.py: FAIL.
The writer never asks the user anything and never edits the data directory beyond its output directory. A report that
fails check.py is not done; rerun the writer rather than editing report.md by hand.
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.

