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 agentmods add commands/nometria/claude-code-plugin/logsgit clone --depth 1 https://github.com/nometria/claude-code-pluginWhat 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 | $0.00009 | $0.00572 |
| Opus 5 | $0.00005 | $0.00286 |
| Sonnet 5 | $0.00002 | $0.00114 |
| Haiku 4.5 | $0.00001 | $0.00057 |
Grade A, and why
logs scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(curl:*), Bash(cat:*), Bash(grep:*), Bash(echo:*), Read What it actually says
View Deployment Logs
Show the user recent deployment and runtime logs for their Nometria app.
Step 1: Resolve token
TOKEN="${NOMETRIA_API_KEY:-${NOMETRIA_TOKEN:-$(grep -s 'NOMETRIA_API_KEY\|NOMETRIA_TOKEN' .env .env.local 2>/dev/null | head -1 | cut -d= -f2- | tr -d ' "'"'"'')}}"
echo "Token found: $([ -n "$TOKEN" ] && echo 'yes' || echo 'no')"
If no token: tell the user to run /nometria-login and stop.
Step 2: Identify the app
cat nometria.json 2>/dev/null
If nometria.json exists, use app_id from it.
If not, or if $ARGUMENTS was provided, list migrations:
curl -s -X POST https://app.nometria.com/listUserMigrations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOKEN" \
-d '{}'
Match by app name if $ARGUMENTS provided. If multiple apps and no argument, ask the user to pick.
Step 3: Fetch logs
curl -s -X POST https://app.nometria.com/getLogs \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOKEN" \
-d "{\"app_id\": \"$APP_ID\"}"
Step 4: Display logs
Format the response clearly:
📋 Logs for <app_name> (<app_id>)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[2026-04-06 12:00:00] npm install completed
[2026-04-06 12:00:05] Build successful
[2026-04-06 12:00:10] PM2 started frontend on port 5173
...
If the response contains no logs, tell the user:
No logs available yet. The app may not be deployed, or logs haven't been generated. Check status with
/statusor deploy with/deploy.
If the API returns an error, show the error and suggest:
Having trouble? Check your app status at https://nometria.com/dashboard Or run
/statusto verify the app is running.
Execute all curl commands and display the results.
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.
- 2d ago First seen · 73 lines · 9 tokens per session scan A 9e4ef9371b7c
logs is a command published in the GitHub repository nometria/claude-code-plugin (3 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 572 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.