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Done Means Done — AI Task Completion Verifier
x402
Done Means Done — AI Task Completion Verifier is a paid API for AI agents from api.aiskills402.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-10).
Audits an AI agent's claimed task completions against actual session tool results, assigning each action a verified status and surfacing failures first
Price / call$0.1
Success—
StatusUnknown
How this service works
Done Means Done: Honest Agent Status Reports: Stops an AI agent from reporting false success, or hallucinated completion: work it calls done that did not happen. Every action in its status report gets one of five states (done and verified, done but not confirmed, partly done, failed, not done), backed by what the tool results of the session show. Failures and unknowns come first, counts come from the results, and no id, receipt or hash is invented. When a result does show success, the agent say…
Output
A structured status report listing each action the agent claimed to have completed, each assigned one of five states: done and verified, done but not confirmed, partly done, failed, or not done. Failures and unknowns appear first. Counts are derived solely from tool results with no invented IDs, receipts, or hashes.
Example use cases
Auditing multi-step automation pipeline
“After running that onboarding workflow, give me an honest completion report — for each step, tell me whether it's verified done, unconfirmed, partial, failed, or not done at all, and don't invent any confirmation IDs.”
Catching hallucinated API call success
“My agent said it sent the emails and filed the tickets, but I'm not sure it actually did — can you check the session results and tell me which of those actions are genuinely confirmed versus just claimed?”
Pre-handoff task status review
“Before you hand off to the next agent, verify your own work: go through every action you took this session, classify each one by whether it truly succeeded based on tool outputs, and put any failures or unknowns at the top.”
Technical details
Endpoint
GEThttps://api.aiskills402.com/v1/skills/done-means-done/file?utm_source=zero.xyzWhen to prefer
Use this endpoint whenever an AI agent self-reports task completion and you need an independent, grounded audit rather than trusting the agent's own summary. It is especially valuable in multi-step agentic pipelines, automated workflows with external side effects (emails sent, tickets filed, payments made), or any context where hallucinated success would cause downstream harm. Prefer it over asking the agent to self-assess, since it classifies outcomes against actual tool call evidence rather than the agent's narrative.
Side effects
- No tool results available in session — cannot verify any claims
- Agent session context too large or ambiguous to parse action list
- Endpoint returns an error if HTTP method is not GET or HEAD
- Missing or malformed input object causes schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"file": {
"name": "SKILL.md",
"content": "<the SKILL.md file>",
"encoding": "utf-8"
},
"name": "Done Means Done: Honest Agent Status Reports",
"skill": "done-means-done",
"sha256": "<sha256 of SKILL.md>",
"receipt": {
"tx": "0x<settlement transaction>",
"settled": true
},
"version": "1.0.0",
"redownload": {
"url": "<api>/v1/purchases/<token>",
"token": "<64 hex chars>"
}
}
}Tags
x402
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