Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aget-framework/template-advisor-agetnpx agentmods add skills/aget-framework/template-advisor-aget/aget-enhance-healthWrote 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/aget-framework/template-advisor-aget/aget-enhance-health)<a href="https://agentmods.dev/skills/aget-framework/template-advisor-aget/aget-enhance-health"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-enhance-health/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/aget-framework/template-advisor-aget/aget-enhance-health"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-enhance-health.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 | $0.00053 | $0.03175 |
| Opus 5 | $0.00026 | $0.01588 |
| Sonnet 5 | $0.00011 | $0.00635 |
| Haiku 4.5 | $0.00005 | $0.00317 |
Grade A, and why
aget-enhance-health 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 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.
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.
This is a copy
100% identical to aget-enhance-health — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aget-enhance-health
Remediate agent health drift. Consumes /aget-check-health output, classifies findings by severity Tier (A/B/C), applies Tier-A in-skill, routes Tier-B to backlog, escalates Tier-C via /aget-file-issue, and re-verifies. Instantiates the canonical check → enhance pipeline (DESIGN_DIRECTION §Principle 9) for the health domain.
This is the Generator layer (ADR-008 step 3), built on /aget-check-health (Advisory/detect) and scripts/health_check.py (implementation substrate). Governing spec: AGET_SESSION_SPEC CAP-SESSION-014.
Input
$ARGUMENTS - Optional check-health output path or invocation flag.
Format:
/aget-enhance-health— run/aget-check-healthinline, then enhance/aget-enhance-health <path-to-json>— consume pre-existing check output/aget-enhance-health --tier A— apply only Tier-A remediations (skip B/C)/aget-enhance-health --dry-run— classify findings but do not remediate
Execution
Phase 0: Diagnose
Objective: Obtain current check-health state. Either consume existing output or run inline.
Execute:
- Check for input JSON path in arguments
- If no input, invoke
/aget-check-health --jsonand capture output:python3 scripts/health_check.py --json > /tmp/aeh_check_$$.json - Parse findings — enumerate each WARN and ERROR
- If no findings (status = HEALTHY): report "No remediation needed" and exit with Skill Completion Signal
User Checkpoint: Present findings summary:
Health Check Findings:
Status: [HEALTHY/WARNINGS/ERRORS]
WARN count: <n>
ERROR count: <n>
Proceed to classification? (yes/adjust/abort)
Exit Criteria: Findings captured. User approved progression or skill exited clean.
Phase 1: Classify (Tier A/B/C)
Objective: Assign severity Tier to each finding per DESIGN_DIRECTION §enhance verb model.
Execute:
- For each finding, evaluate:
- Tier-A (trivially fixable, applied in-skill): ALL of (a) reversible via
git revert, (b) bounded to invoking agent's tree, (c) idempotent - Tier-B (structural-bounded, routed to backlog): affects single artifact but needs broader review or cross-agent input
- Tier-C (scope-affecting, escalated via issue): multi-agent, multi-repo, or policy-level implications
- Tier-A (trivially fixable, applied in-skill): ALL of (a) reversible via
- If a finding is ambiguous between Tiers, default to the higher Tier (more cautious) and document ambiguity
- Produce classification table:
| # | Finding | Tier | Rationale | Proposed Action | |---|---------|:-:|-----------|-----------------|
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 · 273 lines · 53 tokens per session scan A a52bcd290aa5
aget-enhance-health is a skill published in the GitHub repository aget-framework/template-advisor-aget (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 53 tokens to every session and 3,175 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to aget-enhance-health, differing in 6 lines, and is treated as a copy.
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