calendly-cli-skill
AGENTS.md2 starsChanged 9 months agoMITView on GitHub
- Reads credentials
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,774 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repositoryOne other file it gives its agents.
- calendlySkill
The file
We split this AGENTS.md into the rules it gives an agent
11 rules. About 1 is common, 7 are distinctive, and 3 are very specific to this project.
≈1
Common · estimate
Many files like this have a rule of this kind.
≈7
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
- Distinctive: line 10
Do not mark work "done" until PR is merged and issue state verified.
- Distinctive: line 13
Run tests and command help checks.
- Very specific: line 21
Use CALENDLY_API_KEY from env.
- Very specific: line 22
Prefer non-destructive checks first (list*, get*, availability queries).
- Common: line 26
Never hardcode API keys, IDs, or personal data.
- Distinctive: line 27
Use environment variables and placeholders in docs/examples.
- Distinctive: line 28
Keep error messages informative but safe (no token leakage).
- Distinctive: line 32
If behavior changes, update README + SKILL docs in the same PR.
- Distinctive: line 35
Follow existing pattern: MCP-first execution with REST fallback where applicable.
- Very specific: line 36
Keep validation in dedicated src/* helpers with focused unit tests.
- Distinctive: line 37
Prefer additive changes over breaking changes.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md 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
AGENTS.md — calendly-cli-openclaw-skill
Scope
This repo wraps Calendly capabilities for OpenClaw via a generated CLI + targeted custom command logic.
Branch / PR Rules
- Default branch:
main. - One issue per PR branch.
- PR body must include issue linkage:
Closes #N/Fixes #N/Resolves #N. - Do not mark work "done" until PR is merged and issue state verified.
Required PR Quality Gate
- Run tests and command help checks.
- Run
codex review --base main. - Fix all P0/P1/P2 findings.
- Re-run tests/review as needed.
- Merge only when clean.
Calendly Live Validation Policy
For new/changed Calendly commands, run live API smoke tests before merge whenever safe.
- Use
CALENDLY_API_KEYfrom env. - Prefer non-destructive checks first (
list*,get*, availability queries). - For destructive/scheduling E2E tests, use synthetic test identities and immediately clean up (cancel test events).
Safety / Secrets
- Never hardcode API keys, IDs, or personal data.
- Use environment variables and placeholders in docs/examples.
- Keep error messages informative but safe (no token leakage).
Compatibility Policy
- Preserve existing command aliases unless intentionally deprecated.
- If behavior changes, update README + SKILL docs in the same PR.
Implementation Notes
- Follow existing pattern: MCP-first execution with REST fallback where applicable.
- Keep validation in dedicated
src/*helpers with focused unit tests. - Prefer additive changes over breaking changes.
Minimum Verification Commands
bun test./calendly --help./calendly <changed-command> --help- live API smoke test for changed command(s)
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- 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.

