capability-scanner
Skill11 starsChanged 4 months agoMITView on GitHub
Evaluate AI product announcements, model releases, pricing changes, and candidate providers against the AI Capability Reference project's current ontology and scope rules. Use when deciding whether something should be added, updated, watched, or skipped in the reference, especially for consumer-facing AI products, self-hosted runtimes, and open model access.
In this repository5 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- docs/llms.txtllms.txt
- capability-auditSkill
- weekly-roundupSkill
The file
We split this skill into the rules it gives an agent
11 rules. About 0 are common, 7 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Use this skill to assess whether a product, implementation, model-access record, or provider belongs in the AI Capability Reference.
- Distinctive: line 34
Check whether it is consumer-facing, commercially available, or practically usable by an ordinary person.
- Distinctive: line 83
Prefer official sources over press coverage.
- Distinctive: line 84
Do not treat a marketing name as a capability.
- Distinctive: line 85
Do not treat a model family as a product.
- Distinctive: line 86
Do not force open/self-hosted things into one bucket.
- Very specific: line 87
Treat ~1% market share as a heuristic, not a hard threshold.
- Very specific: line 88
Use WATCH for borderline candidates or incomplete evidence.
- Distinctive: line 89
If the case is weak, do not invent certainty.
- Very specific: line 110
If a candidate may belong but does not clearly justify active tracking yet, recommend WATCH rather than ADD.
- Very specific: line 116
Use the capability-audit skill instead when:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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
Capability Scanner
Use this skill to assess whether a product, implementation, model-access record, or provider belongs in the AI Capability Reference.
Load references/GOVERNANCE.md when:
- a candidate seems borderline
- ontology placement is unclear
- you need the current capability taxonomy or scope heuristic
- you need the current tracked set for comparison
Load references/SCAN_WORKFLOW.md when:
- you are running a broader scan rather than evaluating one candidate
- you need signal-gathering guidance
- you need source-priority or recommendation conventions
Core Job
For each candidate:
- Determine what kind of thing it is.
- Check whether it is consumer-facing, commercially available, or practically usable by an ordinary person.
- Assess whether tracking it would materially help the audience understand capabilities, access, constraints, or deployment choices.
- Recommend one of:
ADD,UPDATE,WATCH,SKIP. - Cite the best available sources, preferring official sources.
Output Format
Use this structure:
CANDIDATE: [brief name]
ENTITY TYPE: [Capability | Implementation | Product | Provider | Plan | Surface | Deployment Mode | Model Access | Constraint]
PROVIDER: [if applicable]
PRODUCT: [if applicable]
WHAT CHANGED:
[1-2 sentence summary]
ONTOLOGY FIT:
- Why this entity type is correct
- Any entity-type ambiguity that remains
CAPABILITY MAPPING:
- [capability slug]
- [capability slug]
SCOPE ASSESSMENT:
- Commercially available or practically usable: [Yes/No + reason]
- Audience relevance: [Yes/No + reason]
- Affects capability, access, or deployment choice: [Yes/No + reason]
RECOMMENDATION: [ADD | UPDATE | WATCH | SKIP]
RATIONALE:
- [short point]
- [short point]
EVIDENCE:
- [Official source]
- [Official source]
- [Secondary source, if useful]
OPEN QUESTIONS:
- [only if needed]Decision Rules
- Prefer official sources over press coverage.
- Do not treat a marketing name as a capability.
- Do not treat a model family as a product.
- Do not force open/self-hosted things into one bucket.
- Treat
~1% market shareas a heuristic, not a hard threshold. - Use
WATCHfor borderline candidates or incomplete evidence. - If the case is weak, do not invent certainty.
What To Look For
Good candidates usually involve one of these:
- a new consumer-facing product with meaningful public visibility
- a new implementation on an already tracked product
- a pricing or entitlement change that affects user decisions
- a meaningful new surface or deployment option
- an open model family or runtime that real people can select or run locally
Usually skip:
- enterprise infrastructure with no clear end-user product
- API-only changes with no user-facing impact
- minor renames or vague model-quality claims
- obscure releases that do not clear the audience-relevance bar
Watchlist Rule
If a candidate may belong but does not clearly justify active tracking yet,
recommend WATCH rather than ADD. Treat that as a watchlist candidate,
not a failed evaluation.
Related Skill
Use the capability-audit skill instead when:
- You want to check whether existing tracked products are correctly mapped to a capability
- A capability card looks thin (too few products listed) and you want to know why
- You've added a new capability definition and want to populate it from existing data
The scanner evaluates incoming candidates (one at a time, from outside). The capability audit checks internal completeness (systematically, across all tracked products for a given capability).
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.

