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.
git 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/commands/modeled-information-format/mnemonic/recall)<a href="https://agentmods.dev/commands/modeled-information-format/mnemonic/recall"><img src="https://agentmods.dev/badge/commands/modeled-information-format/mnemonic/recall/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/recall"><img src="https://agentmods.dev/badge/commands/modeled-information-format/mnemonic/recall.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 | $0.00009 | $0.01770 |
| Opus 5.5 | $0.00004 | $0.00708 |
| Sonnet 5.5 | $0.00002 | $0.00354 |
| Haiku 4.5 | $0.00001 | $0.00177 |
Grade A, and why
recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory
Search first: /mnemonic:search {relevant_keywords}
Capture after: /mnemonic:capture {namespace} "{title}"
Run /mnemonic:list --namespaces to see available namespaces from loaded ontologies.
/mnemonic:recall
Search and recall memories from the mnemonic filesystem.
Arguments
[query]- Optional search term for full-text search--namespace- Filter by namespace (_semantic/decisions, _semantic/knowledge, _semantic/entities, _episodic/incidents, _episodic/sessions, _episodic/blockers, _procedural/runbooks, _procedural/patterns, _procedural/migrations)--tags- Filter by tags (comma-separated)--since- Time filter (7d, 30d, 90d, 1y)--type- Filter by cognitive type (semantic, episodic, procedural)--scope- project, org, or all (default: all)--limit- Maximum results (default: 10)--full- Show full memory content instead of summary
Procedure
Step 1: Parse Arguments
QUERY="${1:-}"
NAMESPACE="${NAMESPACE:-}"
TAGS="${TAGS:-}"
SINCE="${SINCE:-}"
TYPE="${TYPE:-}"
SCOPE="${SCOPE:-all}"
LIMIT="${LIMIT:-10}"
FULL="${FULL:-false}"
ORG=$(git remote get-url origin 2>/dev/null | sed -E 's|.*[:/]([^/]+)/[^/]+\.git$|\1|' | sed 's|\.git$||')
[ -z "$ORG" ] && ORG="default"
Step 2: Build Search Paths
SEARCH_PATHS=""
# Get project name from git remote or directory
PROJECT=$(git remote get-url origin 2>/dev/null | sed -E 's|.*/([^/]+)\.git$|\1|' | sed 's|\.git$||')
[ -z "$PROJECT" ] && PROJECT=$(basename "$(pwd)")
# All memories are under ${MNEMONIC_ROOT}/
# Path structure:
# {org}/{project}/ - project-specific memories
# {org}/ - org-wide memories (shared across projects)
# default/ - fallback when org detection fails
case "$SCOPE" in
project)
SEARCH_PATHS="$HOME/.claude/mnemonic/$ORG/$PROJECT"
;;
org)
SEARCH_PATHS="$HOME/.claude/mnemonic/$ORG"
;;
all|*)
# Search project-specific, then org-wide, then default
SEARCH_PATHS="$HOME/.claude/mnemonic/$ORG/$PROJECT $HOME/.claude/mnemonic/$ORG $HOME/.claude/mnemonic/default"
;;
esac
# Narrow by namespace if specified
if [ -n "$NAMESPACE" ]; then
NEW_PATHS=""
for path in $SEARCH_PATHS; do
NEW_PATHS="$NEW_PATHS $path/$NAMESPACE"
done
SEARCH_PATHS="$NEW_PATHS"
fi
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 · 242 lines · 9 tokens per session scan A 5e7c1807bb10
recall is a command published in the GitHub repository modeled-information-format/mnemonic (23 stars, last pushed 6d ago), licensed MIT. It adds 9 tokens to every session and 1,770 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
dream-defrag
A command for pruning Claude Code’s saved memory files, including MEMORY.md and other memory notes.
context-preload
A command for managing and setting up ContextPreloader.
voice-refresh
Refresh the founder-voice DNA from new Granola meetings (interactive, MCP-backed). Pulls meetings since the last refresh, harvests Assaf-only speech, runs the Stage 2-3 orchestrator, and presents a founder-gated delta. Never auto-writes voice-dna.md.
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
Show memex statistics and status including projects, memos, and pending items.
learn
Command "learn" from datacore-one/datacore, covering /learn, purpose, when to use, usage and quick capture.