Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add avelikiy/great_cto/plugin install great-ctoWrote 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/avelikiy/great_cto/recall)<a href="https://agentmods.dev/commands/avelikiy/great_cto/recall"><img src="https://agentmods.dev/badge/commands/avelikiy/great_cto/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/avelikiy/great_cto/recall"><img src="https://agentmods.dev/badge/commands/avelikiy/great_cto/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 | $0.00027 | $0.01051 |
| Opus 5 | $0.00014 | $0.00526 |
| Sonnet 5 | $0.00005 | $0.00210 |
| Haiku 4.5 | $0.00003 | $0.00105 |
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 yesterday.
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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the great_cto /recall command. Answer "what does this project already know about $ARGUMENTS?" from two places: what HAPPENED (session logs) and what is WRITTEN DOWN (the docs/ tree). A concept the operator half-remembers is as likely to live in an ADR as in a session.
Step 1 — Search session logs
QUERY="${ARGUMENTS:-}"
LOG_DIR=".great_cto/logs"
if [ -z "$QUERY" ]; then
echo "Usage: /recall <keyword>"
echo "Examples: /recall jwt | /recall quota | /recall board | /recall npm"
exit 0
fi
# Search 1: match in concepts frontmatter field (highest precision)
echo "=== Concept matches ==="
grep -ril "concepts:.*${QUERY}" "$LOG_DIR"/session-*.md 2>/dev/null | sort -r | head -10
# Search 2: match in full log body (broader)
echo "=== Body matches ==="
grep -ril "${QUERY}" "$LOG_DIR"/session-*.md 2>/dev/null | sort -r | head -10
Step 1b — Search the documentation
Sessions say what happened; docs/ says what was decided and why. Ranked, not
grepped — an exact-substring match over a hundred and sixty documents returns
either nothing or everything, and neither is an answer.
Zero dependencies: the BM25 index is built in memory per call and runs in about a tenth of a second over this repository's corpus.
QUERY="${ARGUMENTS:-}"
MS="${CLAUDE_PLUGIN_ROOT:-$(ls -d "$HOME"/.claude/plugins/cache/*/great_cto/*/ 2>/dev/null | sort -V | tail -1 | sed 's|/$||')}"
MS="$(ls -d $MS/*/ 2>/dev/null | sort -V | tail -1 | sed 's|/$||')/scripts/lib/memory-search.mjs"
[ -f "$MS" ] || MS="scripts/lib/memory-search.mjs"
if [ -n "$QUERY" ] && command -v node >/dev/null 2>&1 && [ -f "$MS" ]; then
echo "=== Documents ==="
# Prints one of three things, and they are different answers: ranked hits,
# "no matches in N documents" (the corpus was read and holds nothing), or
# "nothing to search" (this project has no docs/ at all).
node "$MS" "$QUERY" --source docs --limit 6
fi
Step 2 — Display results
For each unique matching file (deduplicate concept + body matches), show:
- Filename (date + slug)
concepts:frontmatter field (if present)## Donesection bullets (first 5)## Decisionssection (first 3 bullets)
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.
- yesterday Changed 222517c0a276
- 5d ago First seen · 99 lines · 27 tokens per session scan A f1e033ea04be
recall is a command published in the GitHub repository avelikiy/great_cto (89 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 1,051 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 2026-09-03.
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