opencode-delegate
AGENTS.md0 starsChanged 31 days agoMITView on GitHub
This repository maintains one portable Agent Skill: opencode-delegate . It runs opencode as a bounded headless delegate and returns a JSON manifest. All maintained repository content is written in English except README.ru.md, the Russian translation. Read SKILL.md, README.md, QUICKSTART.md, scripts/delegate_opencode.py, and references/. - Invoke via python scripts/delegate_opencode.py --cwd <abs-dir> --task <text> [--timeout ...]. - subprocess.run([...], shell=False) only — no shell. - Honor OPENCODE_BIN before PATH and well-known install locations. - Print a JSON manifest; the human-facing result lives under response.…
- 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 31,700 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.
- opencode-delegateSkill
The file
We split this AGENTS.md into the rules it gives an agent
6 rules. About 0 are common, 1 is distinctive, and 5 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.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 5
All maintained repository content is written in English except README.ru.md, the Russian translation.
- Very specific: line 10
Read SKILL.md, README.md, QUICKSTART.md, scripts/delegate_opencode.py, and references/.
- Distinctive: line 26
Default: no auto-approve, no full-access, no permission bypass flags.
- Very specific: line 27
Never read or print credentials: API keys, tokens, .env*, auth.json, private keys, browser profiles, vendor credential stores.
- Very specific: line 34
Run python -m unittest discover -s tests -v before publishing changes.
- Very specific: line 35
Keep index.json and .well-known/agent-skills/index.json in sync.
≈ “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
Repository instructions
This repository maintains one portable Agent Skill: opencode-delegate
. It runs
opencode as a bounded headless delegate and returns a JSON manifest.
All maintained repository content is written in English except README.ru.md,
the Russian translation.
Read before editing
Read SKILL.md, README.md, QUICKSTART.md,
scripts/delegate_opencode.py, and references/.
Wrapper contract
- Invoke via
python scripts/delegate_opencode.py --cwd <abs-dir> --task <text> [--timeout ...]. subprocess.run([...], shell=False)only — no shell.- Honor
OPENCODE_BINbefore PATH and well-known install locations. - Print a JSON manifest; the human-facing result lives under
response. - Exit codes:
2bad cwd,127binary missing,124timeout,126start failure,65missing/unusable response after claimed success, else the child process exit code. - Temp output dirs use the
opencode-delegate -prefix.
Safety posture
- Default: no auto-approve, no full-access, no permission bypass flags.
- Never read or print credentials: API keys, tokens,
.env*,auth.json, private keys, browser profiles, vendor credential stores. - Delegated output is unverified — check
git diffand tests before accepting. - A delegated agent must not re-delegate to the same CLI in a loop.
Validation and packaging
Run python -m unittest discover -s tests -v before publishing changes.
Keep index.json and .well-known/agent-skills/index.json in sync; rebuild
dist/ and refresh the sha256 digest whenever the payload changes.
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.

