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/doctor)<a href="https://agentmods.dev/commands/avelikiy/great_cto/doctor"><img src="https://agentmods.dev/badge/commands/avelikiy/great_cto/doctor/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/doctor"><img src="https://agentmods.dev/badge/commands/avelikiy/great_cto/doctor.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 | $0.00029 | $0.09260 |
| Opus 5 | $0.00015 | $0.04630 |
| Sonnet 5 | $0.00006 | $0.01852 |
| Haiku 4.5 | $0.00003 | $0.00926 |
Grade A, and why
doctor scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
LATEST=$(curl -fsS --max-time 3 https://registry.npmjs.org/great-cto/latest 2>/dev/null \ How it starts
The opening of the file, as written. The whole thing — 719 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Doctor. Produce a concise, actionable health report for the great_cto pipeline in this project. Do NOT fix — only diagnose and point. Reports go to stdout; no files written.
Setup
source .great_cto/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
FIX_MODE=false
SKILLS_DETAIL=false
SKILLS_REFRESH=false
for arg in "$@"; do
case "$arg" in
--fix) FIX_MODE=true ;;
--skills) SKILLS_DETAIL=true ;;
--skills-refresh) SKILLS_REFRESH=true; SKILLS_DETAIL=true ;;
esac
done
TODAY=$(date +%Y-%m-%d)
NOW_EPOCH=$(date +%s)
Check 1 — Required files
REQ_FILES=(.great_cto/PROJECT.md)
MISS=0
for f in "${REQ_FILES[@]}"; do
if [ ! -f "$f" ]; then
echo "MISSING: $f — run /start (new) or /audit (existing repo)"
MISS=$((MISS+1))
fi
done
Exit early with summary if PROJECT.md missing — no point checking the rest.
Check 2 — PROJECT.md format (v1.0.76+ contract)
# Use bash -c to avoid zsh nomatch + grep-c "0 || echo 0" doubling quirks.
if [ -f .great_cto/PROJECT.md ]; then
HAS_STACK=$(grep -c "^Stack:" .great_cto/PROJECT.md 2>/dev/null); HAS_STACK=${HAS_STACK:-0}
HAS_TYPE=$(grep -c "^Type:" .great_cto/PROJECT.md 2>/dev/null); HAS_TYPE=${HAS_TYPE:-0}
HAS_ARCHETYPE=$(grep -c "archetype:" .great_cto/PROJECT.md 2>/dev/null); HAS_ARCHETYPE=${HAS_ARCHETYPE:-0}
echo "PROJECT.md format:"
[ "${HAS_STACK}" -gt 0 ] && echo " ✓ Stack: line present" || echo " ⚠ Stack: line missing — old format, run /audit to migrate"
[ "${HAS_TYPE}" -gt 0 ] && echo " ✓ Type: line present" || echo " ⚠ Type: line missing — old format, run /audit to migrate"
[ "${HAS_ARCHETYPE}" -gt 0 ] && echo " ✓ archetype: present" || echo " ⚠ archetype: missing"
fi
Check 2c — Archetype confidence
if [ -f .great_cto/PROJECT.md ]; then
CONFIDENCE=$(grep "^archetype_confidence:" .great_cto/PROJECT.md 2>/dev/null | awk '{print $2}')
ALTERNATIVES=$(grep "^archetype_alternatives:" .great_cto/PROJECT.md 2>/dev/null | sed 's/.*\[//;s/\]//')
echo "Archetype confidence:"
case "${CONFIDENCE:-}" in
high)
echo " ✓ archetype_confidence: high — detector is certain"
;;
medium|low)
echo " ⚠ archetype_confidence: ${CONFIDENCE} — consider reviewing alternatives: ${ALTERNATIVES:-none}"
echo " Run /audit to re-detect, or set archetype: manually in .great_cto/PROJECT.md"
;;
user-specified)
echo " ✓ archetype_confidence: user-specified — manually confirmed"
;;
"")
echo " ⚠ archetype_confidence: missing — upgrade to v1.0.146+ and re-run bootstrap"
echo " Quick fix: run \`npx great-cto\` in the project directory"
;;
*)
echo " ⚠ archetype_confidence: unknown value '${CONFIDENCE}' — expected high | medium | low | user-specified"
;;
esac
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.
- 3d ago Changed b0baefb4b436
- 7d ago First seen · 719 lines · 29 tokens per session scan A 9cea27d6f908
doctor is a command published in the GitHub repository avelikiy/great_cto (92 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 9,260 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
bugfix
TDD-driven bugfix workflow: tester writes failing test (RED) → developer fixes (GREEN) → developer refactors (REFACTOR) → reviewer validates. Accepts issue number, description, or both. Auto-creates PR unless --no-pr flag is passed.
fec-debug
Front-end problem diagnosis and repair: covering build failures, runtime errors, UI exceptions, and interface problems, using a unified diagnostic framework to classify problems by type.
fec-tdd
Use front-end TDD workflow to implement functions, fix bugs, or refactor logic: first write failing tests, then implement minimal code, and then refactor.
dead-code-scan
Scan for dead code, unused imports, duplicates, and zombie code across the project.
esp-debug
Help debug ESP32 crashes, hangs, and peripheral issues.
develop
Implement skill development issues with TDD-governed workflow.