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 tranhieutt/software_development_department --skill agent-healthgit clone --depth 1 https://github.com/tranhieutt/software_development_departmentWrote 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/tranhieutt/software_development_department/agent-health)<a href="https://agentmods.dev/skills/tranhieutt/software_development_department/agent-health"><img src="https://agentmods.dev/badge/skills/tranhieutt/software_development_department/agent-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/tranhieutt/software_development_department/agent-health"><img src="https://agentmods.dev/badge/skills/tranhieutt/software_development_department/agent-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 | $0.00041 | $0.01343 |
| Opus 5 | $0.00020 | $0.00672 |
| Sonnet 5 | $0.00008 | $0.00269 |
| Haiku 4.5 | $0.00004 | $0.00134 |
Grade A, and why
agent-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 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Health
Display a performance summary table from production/traces/agent-metrics.jsonl,
cross-referenced with production/session-state/circuit-state.json for live
circuit breaker states.
Steps
1. Parse arguments
| Flag | Default | Description |
|---|---|---|
--session <branch> |
current branch | Filter entries by session field |
--agent <name> |
all | Show only this agent |
--since <date> |
no limit | Only entries with date >= YYYY-MM-DD |
--log |
false | If set, append a fresh metrics snapshot to agent-metrics.jsonl |
Get current branch: git branch --show-current.
2. Read data sources
Read both files in parallel:
production/traces/agent-metrics.jsonl— historical metrics per agent per sessionproduction/session-state/circuit-state.json— live circuit breaker states
If agent-metrics.jsonl contains only the schema header line (no actual entries):
📭 No agent metrics recorded yet for this session.
Metrics are written when agents use /agent-health --log
or at the end of a session via /save-state.
Circuit breaker states (live):
[show table from circuit-state.json only]
3. Aggregate metrics
For each agent, compute across the filtered entries:
total_tasks=tasks_completed+tasks_failed+tasks_blockedsuccess_rate=tasks_completed / total_tasks * 100(0 if no tasks)error_rate= latesterror_ratefield valuecircuit_state= fromcircuit-state.json(live, not from log)
4. Render health table
🏥 Agent Health Report — session: <branch> · <date range>
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Agent Tasks ✅ Done ❌ Failed ⛔ Blocked Success% Circuit
──────────────────────────────────────────────────────────────────────────────
backend-developer 8 7 1 0 87.5% 🟢 CLOSED
frontend-developer 5 5 0 0 100.0% 🟢 CLOSED
qa-engineer 6 4 2 0 66.7% 🟡 HALF-OPEN
data-engineer 2 2 0 0 100.0% 🟢 CLOSED
diagnostics 1 0 1 0 0.0% 🔴 OPEN
──────────────────────────────────────────────────────────────────────────────
TOTAL 22 18 4 0 81.8%
⚠️ Agents needing attention:
🔴 diagnostics — Circuit OPEN · fallback: surface to user
🟡 qa-engineer — Circuit HALF-OPEN · 2 failures this session
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 · 150 lines · 41 tokens per session scan A 386888d6594b
agent-health is a skill published in the GitHub repository tranhieutt/software_development_department (72 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,343 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
playwright-cli
Automates browser interactions for testing and validating your own web applications using playwright-cli. Use when you need terminal-first browser control for navigation, form filling, screenshots, tracing, bound browser sessions, debugging, or generating Playwright test code. Only use against applications you own or…
flutter-ui
Build Flutter UI from Figma MCP or image input. Scans src for design tokens (colors, sizes, text styles), existing components, and naming conventions before writing a single line of code. Never hard-codes values.
serena
Serena code intelligence — LSP-powered symbol navigation, diagnostics, and targeted code surgery. Activate before complex refactors, cross-file analysis, or when graph tools need symbol-level depth.
database-migrations
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).
tdd
Strict test-driven development for behavior changes. Requires verified RED before production code, minimal GREEN, and refactor only after passing tests.
verify
Fresh verification gate before claiming done, fixed, passing, ready, or before commit/PR. Evidence before claims, always.