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 commands/done-0/openarche/knowledge-searchgit clone --depth 1 https://github.com/Done-0/openarcheWhat 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 | $0.00005 | $0.00298 |
| Opus 5 | $0.00003 | $0.00149 |
| Sonnet 5 | $0.00001 | $0.00060 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
knowledge-search 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
Search OpenArche knowledge with repository-local knowledge first and global knowledge as fallback.
Required behavior:
- Find the relevant OpenArche knowledge stores.
If the user is inside a repository, search
.openarche/knowledge/first. Then search the global store under<home>/.claude/openarche/knowledge/. - Read and validate the current config.
- Load the relevant
index.jsonfiles. If a store is missing, treat that store as empty. If a store exists but is invalid, report that the knowledge index is corrupted. - Build the query embedding with the current embedding provider.
- Run vector recall with the configured threshold and topK across the merged search space.
- Expand linked neighbors from the recalled seed entries.
- Prefer current-project knowledge over cross-project knowledge when similarity is close, matching product behavior.
When presenting results, show each match in this form:
[type/structure] id — title
trigger: trigger_context
score: X.X via: vector|link tags: tag1, tag2
If the user asks for more detail, also show:
- source project
- whether the result came from the repository-local or global store
- whether the result came from direct vector recall or link expansion
If both stores are empty, say so plainly.
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 · 37 lines · 5 tokens per session scan A 8e34b0131776
knowledge-search is a command published in the GitHub repository Done-0/openarche (12 stars, last pushed 4mo ago), licensed MIT. It adds 5 tokens to every session and 298 once invoked, about $0.0000 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.
Other commands, from other repositories
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.