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.
npx skills add ashfulcra/fulcra-tools --skill fulcra-agent-operatorgit clone --depth 1 https://github.com/ashfulcra/fulcra-toolsWrote 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/skills/ashfulcra/fulcra-tools/fulcra-agent-operator)<a href="https://agentmods.dev/skills/ashfulcra/fulcra-tools/fulcra-agent-operator"><img src="https://agentmods.dev/badge/skills/ashfulcra/fulcra-tools/fulcra-agent-operator/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/skills/ashfulcra/fulcra-tools/fulcra-agent-operator"><img src="https://agentmods.dev/badge/skills/ashfulcra/fulcra-tools/fulcra-agent-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00059 | $0.01163 |
| Opus 5 | $0.00030 | $0.00581 |
| Sonnet 5 | $0.00012 | $0.00233 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
fulcra-agent-operator 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 10d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fulcra Agent Operator
Enhances fulcra-agent-teams. The failure this skill
kills: an agent hits a wall, quietly parks the work, and the operator never finds out — the workstream is
forgotten. Instead: asks are first-class bus state, an orchestrator nags on them by age, and the
answer is a single deterministic write that puts the work back in motion.
Where to start — the re-entrancy probes
Before surfacing or answering asks, probe whether the engine is usable and whether any asks are
waiting. Enter at the first probe that fails (per the repo's skill-quality pattern,
docs/skill-quality-pattern.md); both probes are pure reads, and the answer leg is a single
idempotent write, so re-entry never corrupts state:
| Probe (run in order) | Command | Passes when | If it fails, enter at |
|---|---|---|---|
| Engine + auth usable? | coord-engine doctor <team> |
exits 0 and the last line is exactly doctor: healthy |
fix engine/auth first (see fulcra-agent-reconcile) — do NOT surface asks against a broken engine |
| Any asks waiting on the operator? | coord-engine asks <team> [--human <id>] |
the header line reads asks — 0 waiting on <id> (oldest first) — nothing to surface (NON-mutating read) |
The orchestrator's duty — a non-zero count means asks are rotting; surface the oldest to the operator and relay the answer per party 2 below |
Both probes clean → the engine is healthy and no ask is waiting; keep polling on your heartbeat.
The three parties
1. Any agent — raising an ask (when you're stuck on the operator)
coord-engine task block <team> <slug> --on-user "<the ask>"
Rules for a GOOD ask (this is the part that makes the loop work):
- Self-contained: someone reading only the ask text can answer it. Include the options ("use vault A or B?"), the default you'd pick, and the consequence of waiting.
- Put longer context in the task body before blocking.
- Then keep working other tasks — blocking one task parks that workstream, not you.
- The answer reaches you on your next wake: it returns to your inbox unblocked, and the delivery
record surfaces in your queue read (
coord-engine queue <team> --agent <you>). Resident listeners are retired — do not wait on one.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 78 lines · 59 tokens per session scan A 25e143426afb
fulcra-agent-operator is a skill published in the GitHub repository ashfulcra/fulcra-tools (10 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 1,163 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
magic-compact
Compact this Claude Code session.
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proof-engine
Create formal, verifiable proofs of claims with machine-checkable reasoning. Use when asked to prove, verify, fact-check, or rigorously establish whether a claim is true or false — mathematical, empirical, or mixed. Trigger phrases: "is it really true", "can you prove", "verify this", "fact-check this", "prove it"…
join
Join the Cortex agent team — reads agent config from team directory, generates .cortex.md protocol, updates CLAUDE.local.md. Idempotent — safe to re-run as a sync.
setup
First-time Cortex setup — creates team directory, config, and chief of staff agent.
leave
Leave the Cortex agent team — removes .cortex.md, cleans CLAUDE.local.md, sets agent status to inactive in team directory.