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/oc/learn-sessionnpx skills add openshift/oc --skill learn-sessiongit clone --depth 1 https://github.com/openshift/ocWhat 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 | $0.00040 | $0.00388 |
| Opus 5 | $0.00020 | $0.00194 |
| Sonnet 5 | $0.00008 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
learn-session scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Review the current conversation to extract knowledge worth persisting for future sessions.
What to look for
- User corrections — where the user redirected the approach, rejected a suggestion, or clarified a preference
- Discovered patterns — implementation patterns, conventions, or architectural knowledge that was hard to find and would save time next session
- Agent/tooling gaps — things the tester or code-reviewer agents should know but don't
What NOT to persist
- Things already documented in AGENTS.md or .claude/agents/
- Code-level details derivable by reading the source
- One-off debugging context that won't recur
- Verbose implementation guides — keep entries brief (1-2 lines for AGENTS.md)
Process
- Read the current state of AGENTS.md and .claude/agents/*.md
- Read the memory index for this project at
~/.claude/projects/$(echo "$PWD" | tr '/' '-')/memory/MEMORY.md(skip if absent) - Review the conversation so far: what was the task, what was learned, what corrections were made
- For each finding, determine where it belongs:
- AGENTS.md — brief convention or rule that applies to all sessions (1-2 lines max)
- .claude/agents/*.md — specific to the tester or code-reviewer agent
- Memory — user preferences, project context, feedback (not code patterns)
- Nowhere — already documented or too specific to recur
- Present the proposed changes for approval. Do NOT write anything until approved.
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.
- 2d ago First seen · 32 lines · 40 tokens per session scan A 3e0f55b8a194
learn-session is a skill published in the GitHub repository openshift/oc (245 stars, last pushed 5d ago), licensed Apache-2.0. It adds 40 tokens to every session and 388 once invoked, about $0.0002 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 2026-08-30.
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