Cell Ontology

Cell Ontology runs two agent workflows and has no skills, subagents, or commands. It is the most useful negative example on this site.

Repository: obophenotype/cell-ontology Product: src/ontology/cl-edit.owl Agent surface: GitHub mention, pull request review

What to look at

Path	What it is
CLAUDE.md	The whole agent configuration
.github/workflows/ai-agent.yml	Runs an agent on a GitHub mention
.github/workflows/clara-review.yml	Reviews pull requests

What works

There is one instructions file. Most repositories in Block A keep the same text in both CLAUDE.md and .github/copilot-instructions.md and have to edit both. Cell Ontology does not have that problem.

CLAUDE.md is specific about search. It tells the agent that cl-edit.owl has one axiom per line, and gives exact grep commands for finding a term by identifier and by label. Concrete commands beat general advice.

It is also specific about identifiers. New term requests use the CL_99xxxxx range, defined in src/ontology/cl-idranges.owl, and the file says never to guess a term identifier or a PubMed identifier.

What to copy first

Copy the search section. Three worked grep examples against your own edit file will save more agent time than a page of prose.

Gaps

Two workflows send real work to the agent, and nothing underneath breaks that work into parts. Every run starts from the same general instructions.

CLAUDE.md contains this line:

DO NOT bother doing your own greps over the file, or looking for other files, unless otherwise asked, you will just waste time.

That is a fix for something that went wrong once, written as a prohibition. A search skill would do the same job and would also tell the agent what to do instead of what to avoid. Prohibitions accumulate; skills compose.

Of the repositories we track, this one would gain the most from a small set of skills. Uberon's identifier-validator and metadata-checker are a reasonable starting pair.