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 redhat-community-ai-tools/harness-eval --skill reviewgit clone --depth 1 https://github.com/redhat-community-ai-tools/harness-evalWrote 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/redhat-community-ai-tools/harness-eval/review)<a href="https://agentmods.dev/skills/redhat-community-ai-tools/harness-eval/review"><img src="https://agentmods.dev/badge/skills/redhat-community-ai-tools/harness-eval/review/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/redhat-community-ai-tools/harness-eval/review"><img src="https://agentmods.dev/badge/skills/redhat-community-ai-tools/harness-eval/review.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 | $0.00058 | $0.01008 |
| Opus 5 | $0.00029 | $0.00504 |
| Sonnet 5 | $0.00012 | $0.00202 |
| Haiku 4.5 | $0.00006 | $0.00101 |
Grade C, and why
review scanned grade C 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 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- evaluator-ignore: content/broken-references, content/allowed-tools-auto-approve --> How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Setup
Full qualitative review of the user's agent setup. Claude reads every file and evaluates quality, redundancy, coherence, and optimization opportunities.
Hard Rules
- Never give a verdict without reading the files. Lint counts are input data, not the verdict. A component with warnings can still be healthy.
- Read before you judge. Read every file's actual content before assessing.
- Don't manufacture problems. If the setup is good, say so.
- Always end with the evidence-based summary.
- Record the exact start time (note the timestamp from your first tool call in Step 2) and compute the exact duration at the end.
Step 1: Ask Output Preference
Before doing anything else, ask the user:
Where should i present the results?
- Terminal - print the report here in the conversation
- File - write a markdown report to a file (you'll choose the path)
Wait for their answer before proceeding.
Step 2: Run Lint for Context
Determine the setup path. If the user doesn't specify one, use the current working directory.
uvx --from harness-eval harness-eval harness-lint <setup-path> --format json
If uvx is not available, fall back to pip install harness-eval and use harness-eval directly.
Read the JSON output. This gives you per-component diagnostics, token budget, trigger overlaps, and dependency findings.
Do NOT present the lint report separately. Use it as context for the qualitative review.
Step 3: Read Actual Files
Read the actual content of every component: SKILL.md files (including reference files in subdirectories), command files, agent files, CLAUDE.md, and settings.json for hooks.
Step 4: Analyze Each Component
For each component, provide:
- Lint results: list each rule that failed and explain WHY it failed in one sentence
- A 2-3 sentence qualitative assessment (what it does, whether it adds value, whether it's well-built)
- Issues found, citing specific content
- Per-component verdict: KEEP, REVIEW, or REMOVE
What ships with it
7 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.
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 · 101 lines · 58 tokens per session scan C 0d5df4f7ee55
review is a skill published in the GitHub repository redhat-community-ai-tools/harness-eval (27 stars, last pushed 3d ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,008 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
ceo-setup
One-time onboarding for the executive/manager commitment workflow — delegation-heavy, meeting prep, decision capture, morning and evening digests. Creates a commitments project and installs two dashboard widgets. After successful setup this skill is excluded from selection until the marker file is deleted.
developer-setup
One-time onboarding for the developer workflow — installs github-workflow missions, creates the commitments workspace, registers per-repo projects, writes calibration memories. After successful setup this skill is excluded from selection until the marker file is deleted.
portfolio
Cross-chain DeFi portfolio discovery, rebalancing suggestions, and NEAR Intent construction. Activates when the user pastes a wallet address or asks about yield/positions/rebalancing. Bootstraps a per-user "portfolio" project, aggregates positions across all the user's addresses inside one project, and offers a…
code-review
Paranoid architect review of code changes for bugs, security, missing tests, and undocumented assumptions. Works on local git diffs OR a GitHub pull request (e.g. owner/repo N). For PRs, can post findings as line-level review comments.
commitment-setup
One-time setup for the commitments tracking system. Creates workspace structure, schema docs, and installs triage and digest missions. Excluded from activation once projects/commitments/README.md exists in the workspace (the file this skill writes as its first step).
content-creator-setup
One-time onboarding for the content creator workflow — content pipeline stages, trend expiration, cross-platform cascades, heavy idea parking. After successful setup this skill is excluded from selection until the marker file is deleted.