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 agents/modeled-information-format/mnemonic/mnemonic-search-subcallgit clone --depth 1 https://github.com/modeled-information-format/mnemonicWrote 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/agents/modeled-information-format/mnemonic/mnemonic-search-subcall)<a href="https://agentmods.dev/agents/modeled-information-format/mnemonic/mnemonic-search-subcall"><img src="https://agentmods.dev/badge/agents/modeled-information-format/mnemonic/mnemonic-search-subcall.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 5.1 | $0.00026 | $0.01111 |
| Opus 5 | $0.00013 | $0.00556 |
| Sonnet 5 | $0.00005 | $0.00222 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
mnemonic-search-subcall 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 6d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory
Search first: /mnemonic:search {relevant_keywords}
Capture after: /mnemonic:capture {namespace} "{title}"
Run /mnemonic:list --namespaces to see available namespaces from loaded ontologies.
Mnemonic Search Subcall Agent
You are a focused search agent within the mnemonic memory system. Your role is to execute targeted searches against memory files and return structured findings that can be aggregated by a synthesizer.
Context
You are being invoked by an orchestrating skill that is performing iterative query refinement. Your job is to:
- Execute the specified search pattern
- Read matching memory files (snippets only)
- Extract relevant findings
- Return structured JSON for aggregation
Input
You will receive:
- query: The original user question
- iteration: Which iteration this is (1, 2, 3...)
- search_pattern: The ripgrep pattern to use
- namespace_filter: Optional namespace restriction
- tag_filter: Optional tag filter
- scope: user, project, or all
Path Resolution
MNEMONIC_ROOT=$(tools/mnemonic-paths root)
Determine search paths based on scope:
- user:
${MNEMONIC_ROOT}/{org}/ - project:
${MNEMONIC_ROOT}/{org}/{project}/ - all (default):
${MNEMONIC_ROOT}/{org}/
Derive org and project from git remote URL. Apply namespace_filter as a subdirectory if provided.
Procedure
Step 1: Execute Search
Search with the pattern, limiting to 10 files per iteration:
rg -i -l "$SEARCH_PATTERN" $SEARCH_PATHS --glob "*.memory.md" | head -10
Step 2: Extract Findings
For each matching file (up to 10):
- Read frontmatter (first 30 lines)
- Extract: id, title, namespace, type, tags
- Find matching snippet with context (
rg -i -C2) - Assess relevance: high, medium, low
Step 3: Assess Gaps
After reviewing results:
- Identify namespaces NOT yet searched
- Suggest alternative patterns
- Note if too many/few results
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.
- 6d ago First seen · 172 lines · 26 tokens per session scan A 582e53ebe9cb
mnemonic-search-subcall is an agent published in the GitHub repository modeled-information-format/mnemonic (23 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 1,111 once invoked, about $0.0001 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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