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/commands/gustavobarbosab/sage/sage-harness-review)<a href="https://agentmods.dev/commands/gustavobarbosab/sage/sage-harness-review"><img src="https://agentmods.dev/badge/commands/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/commands/gustavobarbosab/sage/sage-harness-review"><img src="https://agentmods.dev/badge/commands/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 | $0.00000 | $0.00433 |
| Opus 5 | $0.00000 | $0.00217 |
| Sonnet 5 | $0.00000 | $0.00087 |
| Haiku 4.5 | $0.00000 | $0.00043 |
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 11d 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
Use this prompt to audit your current harness.md for drift, gaps, or inconsistencies.
Harnesses get stale. Conventions evolve. This command catches the mismatch.
Prompt
You are SAGE, a spec-first AI development assistant.
Review the harness.md I'll provide for:
1. Vague or unenforceable rules (rules that can't be checked in code review)
2. Conflicting conventions (rules that contradict each other)
3. Missing common categories (e.g. testing, error handling, navigation)
4. Outdated stack versions or deprecated patterns
5. Anything that would cause inconsistent AI output
For each issue found, format as:
⚠️ <Issue> → <Suggested fix>
Also flag opportunities to strengthen the harness:
💡 <Suggestion> → <Why it would help>
Be specific. Don't tell me "improve naming conventions" — tell me which convention
is unclear and what concrete rule would fix it.
If the harness is solid, say so. Don't manufacture issues.
When to run this
- Every quarter — convention drift is inevitable in active projects
- After a major refactor — your old harness may now describe patterns you've abandoned
- When you notice AI output drifting — if generated code keeps missing a convention, the harness probably doesn't enforce it strongly enough
- Before onboarding a new team member — fresh eyes on the harness reveal what's actually documented vs assumed
After review
For each ⚠️:
- Decide whether to update the harness, update the code, or both
- Commit the harness change with a brief explanation in the message
For each 💡:
- Treat as optional — add if it would genuinely strengthen the AI's output
- Skip if it would over-constrain without clear benefit
Tips
- A harness with no issues is rare and often a sign you've stopped iterating
- Don't add rules just because the AI flagged them — every rule has a maintenance cost
- The best harnesses are short and decisive, not long and exhaustive
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.
- 11d ago First seen · 62 lines · 0 tokens per session scan A e4498c04956c
sage-harness-review is a command published in the GitHub repository gustavobarbosab/sage (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 433 tokens. 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.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.