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 kklimuk/docx-cli --skill weak-agent-testgit clone --depth 1 https://github.com/kklimuk/docx-cliWrote 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/kklimuk/docx-cli/weak-agent-test)<a href="https://agentmods.dev/skills/kklimuk/docx-cli/weak-agent-test"><img src="https://agentmods.dev/badge/skills/kklimuk/docx-cli/weak-agent-test/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/kklimuk/docx-cli/weak-agent-test"><img src="https://agentmods.dev/badge/skills/kklimuk/docx-cli/weak-agent-test.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 | $0.00218 | $0.06656 |
| Opus 5.5 | $0.00087 | $0.02662 |
| Sonnet 5.5 | $0.00044 | $0.01331 |
| Haiku 4.5 | $0.00022 | $0.00666 |
Grade A, and why
weak-agent-test 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 19d 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 — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial review — weak-agent harness for docx-cli
This harness answers one question: can weak agents actually use docx-cli to get
real work done, and what should we fix first? It runs the weak-agent-test
workflow (.claude/workflows/weak-agent-test.js), which fans out one weak exercise
agent per scenario (Haiku by default — swappable to Sonnet via args.model), renders
every output with Microsoft Word, grades each against ground-truth criteria with an
opus judge, and has opus synthesize a prioritized improvement report.
Exercise agents do NOT self-report tool counts — every tool-economy and token number
is measured after the run (agents under-count their own calls ~2×, so self-reports
were dropped): from the agent transcripts for the Claude arms, from each scenario's
exercise.json ledger for the local arm. Both roll up into the same Run-metrics table
(tokens, wall-clock, tool split, correctness) via exercise-metrics.ts.
The test corpus is bundled with this skill under scenarios/, one folder per
scenario, named after its key (scenarios/mnda/, scenarios/invoice/, …). Each
scenario folder is self-describing and holds everything that scenario needs:
task.md— the AGENT-FACING request, written as a human delegating the work: the goal, the data, the intent — and no tool vocabulary (nodocxcommands, locators, or OOXML terms), because discovering which features deliver the outcome is part of what's measured,criteria.md— the JUDGE-ONLY grading rubric (the precise, tool-specific checks). The stage step withholds it from the agent's run workspace, and the judge reads it from the pristine source — the agent never sees the answer key,- the fixture
.docxto work on (edit scenarios only; authoring scenarios create their output fresh), assets/— any additional inputs (data files, images; empty for most edit scenarios).
The workflow's SCENARIOS manifest holds only the per-scenario routing metadata
(key, bucket label, edit/author kind, the doc filename); whether a baseline gets
rendered is DERIVED from the kind (every edit scenario has a pristine source, so it
gets one — see hasBaseline()), not a stored field. The actual
request/criteria/fixture/assets all live in the folder. The skill is
therefore self-contained and travels with its test corpus. To change what a scenario
tests, edit the files in its folder. (Heavy, ephemeral run outputs — edited docx,
renders, reviews, the report — are dumped to ./tmp/docx-weak-agent-test/<ts>/,
never into the repo.)
Staging is ONE code path for every backend: scripts/stage-scenario.ts copies a
scenario folder, strips the judge-only criteria.md, and verifies the inputs landed.
The workflow's Stage agent runs it per scenario; the local corpus runner imports it.
Each run produces, under the timestamped run dir, one result folder per scenario (named after its key) plus the run-level report and metrics:
<RUN_DIR>/
REPORT.md ← synthesized report + the measured run-metrics section, both
written by your post-run exercise-metrics.ts --append-report
exercise-metrics.md ← measured per-exercise-agent tokens/time/tool split
exercise-metrics.json
<key>/ ← one per scenario; the worked-on copy lives here
task.md assets/ ← (criteria.md is withheld from this copy — judge-only)
scratch/ ← the agent's PRIVATE scratch dir (batch JSONL, drafts). The
session scratchpad is shared by every concurrent agent, so
same-named files there collide — see "Isolation breaches"
<doc>.docx ← the edited/authored document
renders/output/ ← the OUTPUT: Word-rendered page PNGs + read.md (markdown read view)
renders/baseline/ ← the pristine "before": page PNGs + read.md (every EDIT scenario;
absent only for the authored eliot-journal — no source to diff)
review.md ← the judge's saved review for this task (written in-run)
verdict.json ← the judge's structured verdict incl. taskSuccess (written in-run
by the judge — the correctness source the metrics pass reads)
metrics.json ← this task's measured tokens/time/tool split + correctness
(written by your post-run metrics pass)
What ships with it
32 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.
- scenarios/contract-finalize/assets/.gitkeep 0 B
- scenarios/contract-finalize/contract-redlined.docx 15 KB
- scenarios/contract-finalize/criteria.md 2.9 KB
- scenarios/contract-finalize/task.md 2.3 KB
- scenarios/contract-markup/assets/.gitkeep 0 B
- scenarios/contract-markup/contract.docx 14 KB
- scenarios/contract-markup/criteria.md 3.6 KB
- scenarios/contract-markup/task.md 3.3 KB
- scenarios/eliot-journal/assets/eliot-poems.md 1.7 KB
- scenarios/eliot-journal/assets/frontispiece.svg 1.4 KB
- scenarios/eliot-journal/criteria.md 3.2 KB
- scenarios/eliot-journal/task.md 3.2 KB
- scenarios/invoice/assets/logo.svg 1.2 KB
- scenarios/invoice/criteria.md 6.9 KB
- scenarios/invoice/invoice.docx 21 KB
- scenarios/invoice/task.md 4.6 KB
- scenarios/mnda/assets/.gitkeep 0 B
- scenarios/mnda/criteria.md 2.1 KB
- scenarios/mnda/mnda.docx 28 KB
- scenarios/mnda/task.md 3.3 KB
- scenarios/resume/assets/.gitkeep 0 B
- scenarios/resume/criteria.md 3.3 KB
- scenarios/resume/resume.docx 28 KB
- scenarios/resume/task.md 3.8 KB
- scripts/collect-exercises.ts 2.4 KB runs code
- scripts/exercise-metrics.ts 42 KB runs code
- scripts/local-exercise-prompt.md 1.5 KB
- scripts/parse-local-ledger.ts 9.0 KB runs code
- scripts/run-local-corpus.ts 15 KB runs code
- scripts/stage-competitor.ts 11 KB runs code
- scripts/stage-scenario.ts 3.4 KB runs code
- scripts/tsconfig.json 667 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.
- 19d ago Changed · +36 lines 7136e184c44f
- 2mo ago First seen · 384 lines · 218 tokens per session scan A 3bdf77be4ca5
weak-agent-test is a skill published in the GitHub repository kklimuk/docx-cli (235 stars, last pushed 2d ago), licensed MIT. It adds 218 tokens to every session and 6,656 once invoked, about $0.0009 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.
Other skills, from other repositories
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
verify
Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.
pptx
Create/edit/inspect/verify slide decks and PPTX presentations.
recipe-save-email-attachments
Find Gmail messages with attachments and save them to a Google Drive folder.
typescript-providers
Implement, modify, test, or document TypeScript provider packages under ts/packages/providers, including framework adapters for OpenAI, Anthropic, Google, LangChain, Mastra, Vercel, LlamaIndex, Cloudflare, Claude Agent SDK, and TypeSafe. Use for provider-specific TS work; do not use for core-only changes.