agent-verification
Skill0 starsChanged 3 months agoMITView on GitHub
Verify that file edits and tool calls actually took effect on disk, instead of trusting success messages. Use whenever the user asks you to "make sure it worked", "verify", "double-check", "did that actually save", "confirm the change", or after you have made a batch of edits and need to report whether they are real.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- vindreshsingh/engineering-skillstheir own version, first seen Oct 20, 2026
- DodoraApp/DodoStreamtheir own version, first seen Oct 8, 2026
- ykq/agent-verificationtheir own version, first seen Sep 2, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- DodoraApp/DodoStream★ 243same name
- vindreshsingh/engineering-skills★ 0same name
- ykq/agent-verification★ 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 repository11 other files it gives its agents.
- claim-evidenceSkill
- crypto-news-digestSkill
- defi-risk-assessmentSkill
- evidence-firstSkill
- flaky-test-detectorSkill
- on-chain-analystSkill
- prompt-injection-hardeningSkill
- refactor-verifierSkill
- skill-security-auditSkill
- smart-contract-reviewSkill
- test-integrity-guardSkill
The file
We split this skill into the rules it gives an agent
9 rules. 0 are common, 7 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
After a batch of file-editing tool calls, before claiming the task is complete.
- Distinctive: line 23
After a tool result that looks odd (an empty diff, a "no change" message, a truncation warning, a batch edit that reported a partial …
- Distinctive: line 25
Before declaring a fix "done" in a PR or commit message.
- Very specific: line 36
Read the file back: Use whatever file-reading tool your environment provides (a "read file" tool, cat, an editor's own re-open) to fetch …
- Distinctive: line 41
Search for the NEW text — it must be there.
- Distinctive: line 42
Search for the OLD text — it must be gone (unless it legitimately appears elsewhere.
- Distinctive: line 48
Check for silent overwrites: If two steps wrote the same file, confirm the final content contains BOTH intended changes, not just the last …
- Very specific: line 78
Large files: verify the changed hunk with a bounded read (an offset/ line-range, or grep -n around the change), not the whole file.
- Distinctive: line 80
Generated/worker output: if a step builds a worker or bundle from a template, the source file can parse fine while the *generated* output …
“Common” is measured: kept by at least 6 in 10 of the 3 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
Agent Verification
The most expensive bug in AI coding is not a wrong line of code — it is an agent reporting "done" when the file on disk never changed. Editors and tool wrappers can return a success result for an edit that silently failed to persist, applied to the wrong file, or was overwritten by a later step. This skill turns "it should have worked" into "here is the proof it did."
When this matters most
- After a batch of file-editing tool calls, before claiming the task is complete.
- Whenever the user asks whether something "actually" happened.
- After a tool result that looks odd (an empty diff, a "no change" message, a truncation warning, a batch edit that reported a partial failure).
- Before declaring a fix "done" in a PR or commit message.
The core rule
A success message is an intention, not a fact. The file is the source of truth. Read it back and compare.
Procedure
- Identify what you claim changed. For every file you edited, note the exact old text → new text (or the write) you intended.
- Read the file back. Use whatever file-reading tool your environment
provides (a "read file" tool,
cat, an editor's own re-open) to fetch the current on-disk content. Never trust an in-memory buffer or the edit tool's own echo of what it thinks it wrote. - Verify the change is actually present.
- Search for the NEW text — it must be there.
- Search for the OLD text — it must be gone (unless it legitimately appears elsewhere; if it does, say so and point at the specific location).
- Check for truncation and partial writes. A batch/multi-file edit with N changes can report failure on one while the others were applied — or, in some tools, roll back everything. Always confirm the END state, not the reported count.
- Check for silent overwrites. If two steps wrote the same file, confirm the final content contains BOTH intended changes, not just the last one.
- Report honestly, with evidence. Say "verified: reading the file back at
path:lineshows the new valueX". If something did NOT apply, say so explicitly and re-do it — never describe a half-applied edit as complete.
Output format
For each file you were asked to verify, produce a short table:
| File | Intended change | Verified? | Evidence |
|-----------------|-----------------------|-----------|------------------------------|
| src/app.ts | foo -> bar | yes | read_file line 42 shows "bar" |
| src/app.ts | remove deprecated fn | no | "old_fn" still present at line 88 |Then one line of verdict: "All changes verified" or "N changes missing — fixing now."
Why this beats the naive approach
"Read the file back" sounds obvious; the value is doing it every time, not just when you feel unsure. The failures this catches are exactly the ones that feel sure: a write to the wrong path, a case-sensitivity mismatch, a batch edit that rolled back, a template literal that silently truncated generated output. They all report success. Only the read-back catches them.
Edge cases
- Large files: verify the changed hunk with a bounded read (an offset/
line-range, or
grep -naround the change), not the whole file. - Generated/worker output: if a step builds a worker or bundle from a template, the source file can parse fine while the generated output is truncated. Verify the artifact, not just the source.
- Case-insensitive filesystems: a rename that changes only case can look like "no change". Check with the exact expected string.
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.

