Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/openshift-online/agent-control-plane/specnpx skills add openshift-online/agent-control-plane --skill specgit clone --depth 1 https://github.com/openshift-online/agent-control-planeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openshift-online/agent-control-plane/spec)<a href="https://agentmods.dev/skills/openshift-online/agent-control-plane/spec"><img src="https://agentmods.dev/badge/skills/openshift-online/agent-control-plane/spec.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00087 | $0.01293 |
| Opus 5 | $0.00044 | $0.00647 |
| Sonnet 5 | $0.00017 | $0.00259 |
| Haiku 4.5 | $0.00009 | $0.00129 |
Grade A, and why
spec scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write or Modify a Spec
Help the user create or change a spec that describes desired system behavior.
User Input
$ARGUMENTS
Before Anything Else
Read the Spec Format Reference below, then follow the phases in order.
Steps
Phase 1 — Frame
Establish the framing before writing anything:
- Desired state only. Ask the user what the system should do, not what's currently broken. If they describe a bug, redirect: "What should the correct behavior be?"
- Scope boundary. Which components does this change touch? (schema, gRPC, runner, operator, CLI, frontend, SDK, RBAC)
- Reserved terms check. Verify no collision with Ambient domain model terms (Inbox, Session, Agent, Project, Credential, SessionMessage, etc.)
Phase 2 — Ground in the codebase
Read actual code and existing specs in the affected areas. Confirm your understanding without wasting the user's time:
- Read existing specs in the target domain
- Grep the components identified in Phase 1
- Summarize back in 3–5 sentences: what you found, what you believe they want, what's ambiguous
- Ask only where the codebase doesn't give a clear answer
Do not proceed to drafting until the user confirms.
Phase 3 — Draft the Spec
Follow the Spec Format Reference below:
- Purpose section — one paragraph describing the domain or feature
- Requirements — each states an observable behavior using RFC 2119 keywords (SHALL, MUST, SHOULD, MAY)
- Scenarios — concrete Given/When/Then examples for each requirement that could be turned into tests
Include: data model, write paths, read paths, RBAC, migration plan for all existing consumers.
Phase 4 — Critic Pass
Spawn critics in parallel per the workflow. Standard critics (every spec change):
- Schema / migration
- RBAC / auth
- Ambient terminology
Plus scope-driven critics based on the components identified in Phase 1.
Phase 5–6 — Synthesize and Present
Separate findings into factual errors (fix directly) and design decisions (present to user with 2–3 concrete options each, one at a time).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 144 lines · 87 tokens per session scan A adce875263d8
spec is a skill published in the GitHub repository openshift-online/agent-control-plane (10 stars, last pushed 5d ago), licensed MIT. It adds 87 tokens to every session and 1,293 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
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review
5-pass structured code review — correctness, security, performance, readability, consistency.
wiki
Markdown-first knowledge base where the LLM acts as librarian. Ingests raw sources, compiles and interlinks topic files, self-maintains an index. No vector DB or embeddings required -- uses LLM-native navigation over structured markdown up to 400K words.
documentation-search
Search the internal knowledge base for runbooks, architecture documentation, ADRs, best practices, and troubleshooting guides using RAG. Use when looking for internal documentation, deployment procedures, architecture decisions, or operational runbooks.