Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/modeled-information-format/mnemonicnpx agentmods add commands/modeled-information-format/mnemonic/searchWrote 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/commands/modeled-information-format/mnemonic/search)<a href="https://agentmods.dev/commands/modeled-information-format/mnemonic/search"><img src="https://agentmods.dev/badge/commands/modeled-information-format/mnemonic/search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/modeled-information-format/mnemonic/search"><img src="https://agentmods.dev/badge/commands/modeled-information-format/mnemonic/search.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00008 | $0.01130 |
| Opus 5.5 | $0.00003 | $0.00452 |
| Sonnet 5.5 | $0.00002 | $0.00226 |
| Haiku 4.5 | $0.00001 | $0.00113 |
Grade A, and why
search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory
Search first: /mnemonic:search {relevant_keywords}
Capture after: /mnemonic:capture {namespace} "{title}"
Run /mnemonic:list --namespaces to see available namespaces from loaded ontologies.
/mnemonic:search
Direct ripgrep search across mnemonic memories.
Arguments
<pattern>- Required. Search pattern (supports regex)--namespace- Limit search to specific namespace--context- Lines of context around matches (default: 0)--files-only- Only list matching file paths--case-sensitive- Case-sensitive search (default: case-insensitive)--scope- user, project, or all (default: all)
Procedure
Step 1: Parse Arguments
PATTERN="${1:?Error: Pattern required}"
NAMESPACE="${NAMESPACE:-}"
CONTEXT="${CONTEXT:-0}"
FILES_ONLY="${FILES_ONLY:-false}"
CASE_SENSITIVE="${CASE_SENSITIVE:-false}"
SCOPE="${SCOPE:-all}"
ORG=$(git remote get-url origin 2>/dev/null | sed -E 's|.*[:/]([^/]+)/[^/]+\.git$|\1|' | sed 's|\.git$||')
[ -z "$ORG" ] && ORG="default"
Step 2: Build Search Command
# Base command
RG_CMD="rg"
# Case sensitivity
[ "$CASE_SENSITIVE" = "false" ] && RG_CMD="$RG_CMD -i"
# Context lines
[ "$CONTEXT" -gt 0 ] && RG_CMD="$RG_CMD -C$CONTEXT"
# Files only
[ "$FILES_ONLY" = "true" ] && RG_CMD="$RG_CMD -l"
# File pattern
RG_CMD="$RG_CMD --glob '*.memory.md'"
Step 3: Determine Search Paths
SEARCH_PATHS=""
case "$SCOPE" in
user)
SEARCH_PATHS="$HOME/.claude/mnemonic/$ORG"
;;
project)
SEARCH_PATHS="./.claude/mnemonic"
;;
all|*)
SEARCH_PATHS="$HOME/.claude/mnemonic/$ORG ./.claude/mnemonic"
;;
esac
# Narrow by namespace
if [ -n "$NAMESPACE" ]; then
NEW_PATHS=""
for path in $SEARCH_PATHS; do
[ -d "$path/$NAMESPACE" ] && NEW_PATHS="$NEW_PATHS $path/$NAMESPACE"
done
SEARCH_PATHS="$NEW_PATHS"
fi
Step 4: Execute Search
echo "=== Searching: $PATTERN ==="
echo ""
for path in $SEARCH_PATHS; do
if [ -d "$path" ]; then
if [ "$FILES_ONLY" = "true" ]; then
rg $([[ "$CASE_SENSITIVE" = "false" ]] && echo "-i") -l "$PATTERN" "$path" --glob "*.memory.md" 2>/dev/null
else
rg $([[ "$CASE_SENSITIVE" = "false" ]] && echo "-i") $([[ "$CONTEXT" -gt 0 ]] && echo "-C$CONTEXT") "$PATTERN" "$path" --glob "*.memory.md" 2>/dev/null
fi
fi
done
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.
- 1mo ago First seen · 179 lines · 8 tokens per session scan A e88b114b6380
search is a command published in the GitHub repository modeled-information-format/mnemonic (23 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 1,130 once invoked, about $0.0000 per session on Opus 5.5. 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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context-preload
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voice-refresh
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q-research
Read the research-mode skill's SKILL.md for the full ruleset before proceeding. Follow all constraints, the source lookup cascade, the token budget, and the "what counts as cited" rules exactly.
status
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learn
Command "learn" from datacore-one/datacore, covering /learn, purpose, when to use, usage and quick capture.