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.
git clone --depth 1 https://github.com/gustavobarbosab/sageWrote 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/rules/gustavobarbosab/sage/sage-harness-review)<a href="https://agentmods.dev/rules/gustavobarbosab/sage/sage-harness-review"><img src="https://agentmods.dev/badge/rules/gustavobarbosab/sage/sage-harness-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/rules/gustavobarbosab/sage/sage-harness-review"><img src="https://agentmods.dev/badge/rules/gustavobarbosab/sage/sage-harness-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 | $0.00016 | $0.00352 |
| Opus 5 | $0.00008 | $0.00176 |
| Sonnet 5 | $0.00003 | $0.00070 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
sage-harness-review 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.
What it actually says
/sage harness review
Audits the current .sage/harness.md for drift, gaps, or inconsistencies.
Instructions
Read .sage/harness.md (or CLAUDE.md, .cursorrules, or project knowledge).
Analyze for:
- Vague or unenforceable rules — rules that can't be checked in code review
- Conflicting conventions — rules that contradict each other
- Missing categories — common gaps: error handling, navigation, testing, string resources
- Outdated stack versions — deprecated patterns or libraries
- Anything that would cause inconsistent AI output — ambiguous rules
Format issues as:
⚠️ <Issue> → <Suggested fix>
Format improvement suggestions as:
💡 <Suggestion> → <Why it would help AI output quality>
If the harness is solid, say so explicitly. Don't manufacture issues.
Rules
- Be specific — "improve naming conventions" is not useful; "the ViewModel naming rule doesn't specify whether test files use
TestorSpecsuffix" is - Don't suggest rules just because they're common — every rule has a maintenance cost
- The best harnesses are short and decisive, not long and exhaustive
After review
Tell the user: "Review complete. For each ⚠️ — decide whether to update the harness, update the code, or both, and commit the change with a brief message. 💡 suggestions are optional — add only what genuinely improves AI output."
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 · 47 lines · 16 tokens per session scan A 147977132787
sage-harness-review is a cursor rule published in the GitHub repository gustavobarbosab/sage (2 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 352 once invoked, about $0.0001 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.
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