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 buildoak/fieldwork-skills --skill trueskill-rankgit clone --depth 1 https://github.com/buildoak/fieldwork-skillsWrote 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/buildoak/fieldwork-skills/trueskill-rank)<a href="https://agentmods.dev/skills/buildoak/fieldwork-skills/trueskill-rank"><img src="https://agentmods.dev/badge/skills/buildoak/fieldwork-skills/trueskill-rank/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/buildoak/fieldwork-skills/trueskill-rank"><img src="https://agentmods.dev/badge/skills/buildoak/fieldwork-skills/trueskill-rank.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 | $0.00061 | $0.02197 |
| Opus 5 | $0.00030 | $0.01099 |
| Sonnet 5 | $0.00012 | $0.00439 |
| Haiku 4.5 | $0.00006 | $0.00220 |
Grade A, and why
trueskill-rank 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 12d 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.
Fallback: If `agent-mux` not found, falls back to direct OpenAI API via `urllib.request` (stdlib, zero deps). Requires `OPENAI_API_KEY` env var. Uses `gpt-4o-mini`. Results written as `{"success": true, "response": "..." How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TrueSkill Rank
Rank any collection of text items by quality using TrueSkill + LLM-as-judge.
Setup
pip install trueskill
- Python 3.11+ required
- agent-mux for parallel dispatch (optional -- falls back to direct OpenAI API if
OPENAI_API_KEYis set) - Claude Code: copy this skill folder into
.claude/skills/trueskill-rank/ - Codex CLI: append this SKILL.md content to your project's root
AGENTS.md
For the full installation walkthrough (prerequisites, verification, API fallback), see references/installation-guide.md.
Staying Updated
This skill ships with an UPDATES.md changelog and UPDATE-GUIDE.md for your AI agent.
After installing, tell your agent: "Check UPDATES.md in the trueskill-rank skill for any new features or changes."
When updating, tell your agent: "Read UPDATE-GUIDE.md and apply the latest changes from UPDATES.md."
Follow UPDATE-GUIDE.md so customized local files are diffed before any overwrite.
Quick Start
PYTHON="python3"
CLI="~/.claude/skills/trueskill-rank/scripts/trueskill-rank.py"
# Full pipeline: prepare + dispatch + aggregate
$PYTHON $CLI run \
--input items.json \
--overlap 3 \
--rubric ~/.claude/skills/trueskill-rank/rubrics/practitioner-signal.md \
--output results.json
# Or step by step:
$PYTHON $CLI prepare --input items.json --overlap 3 \
--rubric ~/.claude/skills/trueskill-rank/rubrics/practitioner-signal.md \
--output-dir /tmp/ts-run/
# Dispatch is handled internally by trueskill-rank.py (no separate script needed)
$PYTHON $CLI aggregate --run-dir /tmp/ts-run/ --output results.json
Cost: each subset of 10 items produces C(10,2)=45 implicit pairwise comparisons. 100 items at overlap 3 = 30 subsets = 30 API calls = 1,350 implicit comparisons.
Decision Tree
Mode Selection
| Question | Answer | Mode |
|---|---|---|
| Ranking individual items (messages, posts)? | Yes | --mode batch (default) |
| Comparing entities (channels, sources, candidates)? | Yes | --mode pairwise |
| Items > 50? | Yes | --mode batch (far more efficient) |
| Items < 20, need binary signal? | Yes | --mode pairwise |
What ships with it
9 files 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.
- references/algorithm.md 3.2 KB
- references/installation-guide.md 1.6 KB
- references/prior-runs.md 1.6 KB
- rubrics/example-template.md 615 B
- rubrics/practitioner-signal.md 1.3 KB
- rubrics/signal-serendipity-entropy.md 1.0 KB
- scripts/trueskill-rank.py 36 KB runs code
- UPDATE-GUIDE.md 1.6 KB
- UPDATES.md 924 B
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.
- 12d ago First seen · 221 lines · 61 tokens per session scan A f46a9e6d005c
trueskill-rank is a skill published in the GitHub repository buildoak/fieldwork-skills (15 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 2,197 once invoked, about $0.0003 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 2026-08-30.
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