corroborate
Skill1 starsChanged 11 days agoMITView on GitHub
Establish what an uncommitted or unfamiliar change actually IS before committing, discarding, pushing, or merging it — by making the artifact testify rather than reading the diff and inferring. Use when handling work you did not author: a dirty working tree, staged changes of unknown provenance, a stale-looking file, an unexplained deletion, an untracked directory, someone else's WIP, or any sweep that ends in "commit what's finished." Also trigger before discarding anything, before committing a whole dirty tree, when a diff looks like a revert, when a deletion has no explanation, or when the user says "clean this up," "commit what's done," "sync the fleet," or "is this safe to commit." Complements touchstone: touchstone challenges a claim of correctness; corroborate establishes what a change is in the first place.
In this repository28 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- claude-md-auditSkill
- cloudflare-oneSkill
- cloudflareSkill
- component-factorySkill
- concurrency-probeSkill
- core-sampleSkill
- decision-telemetrySkill
- disk-auditSkill
- engramSkill
- frontend-designSkill
- git-forensicsSkill
- high-signal-engineSkill
- local-swarmSkill
- model-inventorySkill
- muster-triageSkill
- precise-coding-assistantSkill
- preflightSkill
- pr-triageSkill
- read-arxiv-paperSkill
- run-mazze-leczzare-blogSkill
- session-journalSkill
- shipSkill
- stratum-project-initSkill
- touchstoneSkill
- transcript-handoffSkill
- web-perfSkill
- workspace-syncSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
Every technique below is a way of answering the second half.
≈ “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
corroborate
To corroborate is to confirm a story with independent evidence. Not to find the story plausible — to make something other than the story say the same thing.
What this skill is for
You are about to commit, discard, push, or merge a change you did not author. The diff shows you shape: lines added, lines removed, files touched. Shape is not meaning. A deletion looks the same whether it was deliberate or accidental. A file full of additions looks the same whether it is new work or an old copy written back over new work. An untracked directory looks the same whether it is a rename in progress or scratch.
Acting on shape is how finished work gets discarded and how reverts get committed. This skill is the discipline of asking the artifact itself.
The governing move: every artifact has an authority that is not the diff. Find it and consult it before you act.
The core question
Not "what does this change look like?" but:
What would this be, and how would I tell that apart from what it resembles?
Every technique below is a way of answering the second half.
Techniques, by what you need to know
| Question | Authority to consult | Command |
| Is this a move, or a delete plus new files? | The bytes | hash both sides; identical ⇒ rename |
| Is this content new, or a copy of something older? | Git history | git log -S "<exact string>" -- <path> |
| Does this data belong in this project? | The project's own validator | run it — projects that have one are telling you to use it |
| Is this finished? | Its test suite | run it; "it looks done" is not a result |
| Was this deletion deliberate? | Why the file arrived | git log -1 -- <path> — a file added on purpose and deleted without explanation is an accident until proven otherwise |
| Is this working tree stale? | Timestamps against history | compare file mtime to the commits it lacks |
| Would committing this revert someone? | The diff's direction | in git diff, - is committed and + is your tree; a + that restores older text is a revert wearing the costume of an edit |
| Is it safe to discard? | Whether git already has it | if the content exists in any commit, discarding loses nothing recoverable |
The decision rule
Two questions, in order:
- Does this content exist anywhere else? In a commit, on a remote, in a backup. If yes, discarding is cheap and reversible. If no, it exists in one place and nothing may be done casually.
- Does committing it move the repository forward or backward? Forward ⇒ commit. Backward ⇒ discard, and say what it would have reverted.
A change can be large, plausible, and entirely a revert. Size is not direction.
Anti-patterns
git add -Aon a tree you did not author. It commits the reverts along with the work, and the two are indistinguishable afterwards.- Treating untracked as new. Untracked means git has not been told about it — often it is half of a rename whose other half is a pending deletion.
- Inferring intent from the commit message of the change you are making. You are writing that message. It is not evidence.
- Asking a model to judge the diff instead of running the thing. Use a local model to summarise a large diff; do not let a summary stand in for a validator or a test suite that exists and could just be run.
- Reporting "clean" after a sweep without saying what was left and why. A clean tree that was achieved by discarding someone's work is worse than a dirty one.
Worked examples
Each of these looked like something it was not.
A rename hiding as a deletion. Two docs deleted; an untracked directory
containing two files with the same names. Plausible as either a move or a
delete-plus-rewrite. Hashed both sides against HEAD — byte-identical, so a
true rename. Committed with git add -A of both paths, and git recorded R.
Had they differed, it would have been a move plus an edit and needed reading.
New work that was a revert. Two SKILL.md files, one +149/-16 — every
appearance of substantial new content. git log -S on the exact added strings
returned a commit named "vendor skill set as installed (pre-consolidation)".
The working tree was an older vendored copy written back over a consolidation.
Committing it would have destroyed the consolidation; the +149 was the
give-away only once its provenance was checked. Confirmed twice: the history
search, and the fact that the installed skills matched HEAD, not the tree.
Data whose validity was checkable. An untracked *-trace.jsonl in a
project whose CI validates every trace. Rather than guess whether it was real
or scratch, ran the project's own validate-trace.py: "trace loads clean;
every guard passed; projection is total." That made it committable and proved
CI would accept it.
Finished work that looked abandoned. Staged changes two weeks old, no
branch, no PR. Ran the suite: 32 passing, including 4 new tests, with a written
decision entry. Not abandoned — stranded, by a stale .git/index.lock dated
the day after the work. Committed with the cause recorded, so the timestamps
make sense to whoever reads the log next.
When a sweep is finished
Report three lists, not one:
- Resolved — with what made each safe.
- Left, with reasons — mid-edit, needs a decision, out of scope. Naming the reason is what distinguishes leaving something from missing it.
- What you discarded and what it would have done — never silent.
Perimeter
This establishes what a change is, not whether it is correct — for that, touchstone. It cannot help where the artifact has no authority to consult: no tests, no validator, no history, content that exists nowhere else. In that case the honest answer is that it cannot be corroborated, and it belongs on the "needs a human" list rather than being committed on a hunch.
It also assumes git history is trustworthy. Against a rewritten or force-pushed
history, git log -S proves less than it appears to.
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.

