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 darkroomengineering/cc-settings --skill proof-of-workgit clone --depth 1 https://github.com/darkroomengineering/cc-settingsWrote 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/darkroomengineering/cc-settings/proof-of-work)<a href="https://agentmods.dev/skills/darkroomengineering/cc-settings/proof-of-work"><img src="https://agentmods.dev/badge/skills/darkroomengineering/cc-settings/proof-of-work/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/darkroomengineering/cc-settings/proof-of-work"><img src="https://agentmods.dev/badge/skills/darkroomengineering/cc-settings/proof-of-work.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 | $0.00050 | $0.01057 |
| Opus 5.5 | $0.00020 | $0.00423 |
| Sonnet 5.5 | $0.00010 | $0.00211 |
| Haiku 4.5 | $0.00005 | $0.00106 |
Grade A, and why
proof-of-work scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proof of Work
The Amdahl-shrink move from the Orchestration Tax: human review is the serial bottleneck, so don't spend it confirming what a machine can verify. An agent's diff is review-ready only when the machine-verifiable battery is green — types, tests, lint (and a screenshot for UI). What a machine can prove shouldn't cost a human's attention.
The gate
Run the battery on the current working tree:
PROOF_RUNNER="${CODEX_HOME:-$HOME/.codex}/darkroom/source/src/scripts/proof.ts"
[ -f "$PROOF_RUNNER" ] || PROOF_RUNNER="$HOME/.claude/src/scripts/proof.ts"
bun "$PROOF_RUNNER"
This is the portable installed runner — it works in any repo. (bun run proof is a shortcut that only exists inside the cc-settings repo itself; don't reach for it in a consumer project.) It detects typecheck / test / lint from the project's package.json, runs them cheapest-first, and prints one verdict:
- exit 0 →
review-ready ✓ - exit 1 →
NOT review-ready ✗— fix the failing gate before a human looks
Projects can opt into advisory probes by depending on the tool — the gate then runs the project's pinned binary: react-doctor (React render/quality score, telemetry off) and/or deslop (framework-agnostic cross-file dead-code count). Advisory results are reported but never flip the verdict — deterministic signals alongside the hard gates, not blockers. Silent for projects that don't depend on them.
For UI changes, attach a screenshot (via the chrome-devtools MCP) as the visual half of the proof — tests can't prove "looks right".
Standalone Codex semantic probe
Use spawn_agent to create a fresh read-only reviewer, send_message to
deliver context while it runs, followup_task to trigger another turn once it
is idle, wait_agent to wait, and interrupt_agent only to stop its current
turn. Treat findings as advisory beside
the mechanical verdict. Never spawn codex-verifier and never run codex-run.ts from inside Codex.
Skip the Claude bridge branch below.
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.
- 9d ago Changed 46456dcb2ebf
- 13d ago Changed 4aee7e0119e1
- 21d ago Changed 560b06d09171
- 1mo ago Changed · -6 tokens per session 95ea7dcff710
- 2mo ago First seen · 66 lines · 56 tokens per session scan A bd3ce976b274
proof-of-work is a skill published in the GitHub repository darkroomengineering/cc-settings (52 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 1,057 once invoked, about $0.0002 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.
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