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/aigentive/ralphx/knowledge-capturenpx skills add aigentive/RalphX --skill knowledge-capturegit clone --depth 1 https://github.com/aigentive/RalphXWhat 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 | $0.00070 | $0.00805 |
| Opus 5 | $0.00035 | $0.00402 |
| Sonnet 5 | $0.00014 | $0.00161 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
knowledge-capture 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.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Capture
Packages session learnings into scoped .claude/rules/ files.
Step 1: Read Framework Reference
Read the memory framework doc for knowledge capture criteria and format:
${CLAUDE_PLUGIN_ROOT}/memory-framework.md
Also fetch/refresh the official Claude Code memory docs (cached locally):
"${CLAUDE_PLUGIN_ROOT}/skills/rule-manager/scripts/rule-fetch-docs.sh"
Step 2: Evaluate Session
Review the current session's conversation to identify:
Worth Capturing
- Complex multi-component interactions (e.g., "Component A triggers Event B which updates State C")
- Error recovery procedures that took multiple attempts to resolve
- Deep internal system knowledge (state machines, data flows, edge cases)
- Framework/library quirks and workarounds (e.g., React ref equality, Tauri serialization)
- Patterns that would save >15 minutes if known upfront next time
NOT Worth Capturing
- One-off fixes unlikely to recur
- Knowledge already documented in existing .claude/rules/ files
- Generic programming knowledge (things Claude already knows)
- Temporary workarounds that should be fixed properly
- Simple bug fixes with obvious causes
If nothing worth capturing -> output "No significant learnings to capture." and stop.
Step 3: Classify Each Learning
For each learning worth capturing, determine:
3a. Scope (which files does it relate to?)
- Identify the files that were involved in the discovery
- Determine glob patterns that cover those files
- Example: discovery about TaskGraph -> paths: ["src/components/TaskGraph/**"]
3b. Existing Rule Check
Run the audit script to see current rules:
"${CLAUDE_PLUGIN_ROOT}/skills/rule-manager/scripts/rule-audit.sh" --json
Check if any existing rule file covers the same domain:
- If yes -> append to that file (add new ## section)
- If no -> create new file
3c. Format Entry
Use the auto-memory style format:
## [Descriptive Title]
- **Problem**: What went wrong or was complex
- **Fix**: How it was resolved
- **File**: Key file paths involved (e.g., `src/components/TaskGraph/TaskGraphView.tsx`)
- **Pattern**: Reusable principle (if applicable)
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 · 109 lines · 70 tokens per session scan A 1878b16decda
knowledge-capture is a skill published in the GitHub repository aigentive/RalphX (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 70 tokens to every session and 805 once invoked, about $0.0003 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.
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