Borrowing it
Nothing to install: this file belongs to kryptobaseddev/cleo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kryptobaseddev/cleo/main/.claude/commands/orchestrate-saga.mdgit clone --depth 1 https://github.com/kryptobaseddev/cleoWrote 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/kryptobaseddev/cleo/orchestrate-saga)<a href="https://agentmods.dev/commands/kryptobaseddev/cleo/orchestrate-saga"><img src="https://agentmods.dev/badge/commands/kryptobaseddev/cleo/orchestrate-saga/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/kryptobaseddev/cleo/orchestrate-saga"><img src="https://agentmods.dev/badge/commands/kryptobaseddev/cleo/orchestrate-saga.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 | $0.00019 | $0.02700 |
| Opus 5.5 | $0.00008 | $0.01080 |
| Sonnet 5.5 | $0.00004 | $0.00540 |
| Haiku 4.5 | $0.00002 | $0.00270 |
Grade A, and why
orchestrate-saga 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 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.
Asks the agent to reveal its instructionslowSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
- **"Show full prompt"** — `cat` the file to the conversation Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate Saga
Generate a strict, structured Prime-Orchestrator goal prompt for the saga in $ARGUMENTS and lock it via /goal. Generated prompt MUST be ≤3900 characters. Target 3700 for safety.
Argument parsing
First token = saga ID (e.g. T10176). Optional flags:
--docs <comma-list>— research doc slugs to include--decisions <comma-list>— memory decision IDs to include- Anything else = free-text intent appended to the generated prompt's final line
If --docs omitted, auto-discover via cleo docs find "<sagaTitle>". If --decisions omitted, auto-discover via cleo memory find "<sagaTitle>" --type decision.
Execute in order
Step 1 — Gather saga context (read-only, batched in ONE bash block)
SAGA="<sagaId from $ARGUMENTS>"
cleo show $SAGA 2>&1 | python3 -c "import json,sys; d=json.load(sys.stdin)['data']; t=d['task']; print(f\"TITLE={t['title']}\"); print(f\"AC_COUNT={len(t.get('acceptance',[]))}\"); print(f\"STATUS={t['status']}\")"
cleo saga rollup $SAGA 2>&1 | python3 -c "import json,sys; d=json.load(sys.stdin)['data']; print(f\"TOTAL={d['total']} DONE={d['done']} PCT={d['completionPct']}\")"
# Try saga groups relation first; fall back to parent-edge enumeration if empty.
MEMBERS=$(cleo saga members $SAGA 2>&1 | python3 -c "import json,sys; d=json.load(sys.stdin)['data']
ms = d.get('members', d.get('items', []))
out = []
for m in ms:
if isinstance(m, dict) and m.get('id'):
out.append(f\"EPIC {m['id']} {(m.get('title') or '')[:60]}\")
print('\n'.join(out))")
if [ -z "$MEMBERS" ]; then
# Fallback: enumerate child Epics via parent edge.
# T9658 wired `cleo list --parent <saga>` through saga.groups in packages/core/src/tasks/list.ts,
# so this branch + the primary `cleo saga members` cover every shipped saga shape.
MEMBERS=$(cleo list --parent $SAGA --limit 50 2>&1 | python3 -c "import json,sys; d=json.load(sys.stdin)['data']
for t in d['tasks']:
if t.get('type') == 'epic':
rollup = t.get('childRollup', {})
nt = rollup.get('total', 0) if isinstance(rollup, dict) else 0
print(f\"EPIC {t['id']} {t['title'][:55]} ({nt}t)\")")
fi
if [ -z "$MEMBERS" ]; then
echo "WARN: could not auto-enumerate Epic members for $SAGA. Ask user to supply --epics T9978,T9979,..."
exit 2
fi
echo "$MEMBERS"
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 Changed 5a61ea220459
- 1mo ago First seen · 189 lines · 19 tokens per session scan A 6fd85ad0a930
orchestrate-saga is a command published in the GitHub repository kryptobaseddev/cleo (159 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 2,700 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.
speckit.bug.test
Validate that a previously fixed bug is resolved and record the verification report.