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/one-armed-boy/auto-knowledge-sync-mcp/auto-knowledge-syncnpx skills add One-armed-boy/auto-knowledge-sync-mcp --skill auto-knowledge-syncgit clone --depth 1 https://github.com/One-armed-boy/auto-knowledge-sync-mcpWrote 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/one-armed-boy/auto-knowledge-sync-mcp/auto-knowledge-sync)<a href="https://agentmods.dev/skills/one-armed-boy/auto-knowledge-sync-mcp/auto-knowledge-sync"><img src="https://agentmods.dev/badge/skills/one-armed-boy/auto-knowledge-sync-mcp/auto-knowledge-sync.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 | $0.00065 | $0.00802 |
| Opus 5 | $0.00032 | $0.00401 |
| Sonnet 5 | $0.00013 | $0.00160 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
auto-knowledge-sync 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 3d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Knowledge Sync
Read lane
- Call
search_knowledgeonce near the start of a relevant technical task. Generalize the query and omit company, customer, repository, host, ticket, person, credential, private path, and other identifying details. - If a match is relevant, use
get_knowledgewhen the full entry or evidence is needed. Inspect status, version scope, evidence, contradictions, and volatility. - Treat the result as prior knowledge, not current authority. Verify changeable claims against authoritative public sources before relying on them.
- Continue the primary task without delay when the MCP server is unavailable or no compatible match exists.
Typical triggers include:
- comparing libraries, protocols, storage engines, or deployment approaches;
- diagnosing a recurring failure mode or version-specific behavior; and
- choosing an architecture, dependency, compatibility range, or operational pattern.
Do not search for trivial edits, purely stylistic work, or requests where stored technical knowledge cannot affect the result.
Write lane
Keep writing separate from retrieval. Do not capture every thought or use the repository as a draft inbox.
- When a conclusion is stable, portable, and useful to another engineer, call
prepare_captureimmediately so the complete canonical skeleton is available before the session budget is low. - Infer the language of the latest substantive user message and use it for every human-readable title, claim, attestation, and prose section unless the user explicitly requests another language. Pass that BCP 47 tag to
prepare_capturewhen practical; its defaultautohas the same policy. Keep canonical headings, enum values, IDs, version constraints, and code identifiers unchanged. - Do not send the conversation transcript to the MCP server for language detection. Infer language in the host and submit only the completed knowledge payload.
- If a separate subagent is available, delegate filling or reviewing the skeleton while the primary task continues. Keep final privacy, completeness, portability, and approval decisions in the current session.
- Replace every skeleton marker. Explain the concept, operation, significance, problem solved, constraints, failure modes, alternatives, version scope, and verification. Add a newly authored synthetic example only when it improves understanding.
- Never send credentials, private URLs or paths, proprietary identifiers, internal topology, copied internal source code, or incomplete candidate notes. Generalize private-context observations and complete the portability attestation honestly.
- Call
capture_knowledge, inspect every gate result, and useapply_proposalonly when the configured approval flow requires and permits it.
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.
- 3d ago First seen · 46 lines · 65 tokens per session scan A 180bc6911963
auto-knowledge-sync is a skill published in the GitHub repository One-armed-boy/auto-knowledge-sync-mcp (0 stars, last pushed 10d ago), licensed Apache-2.0. It adds 65 tokens to every session and 802 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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