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 agents/paruff/ufawkesai/measuregit clone --depth 1 https://github.com/paruff/uFawkesAIWrote 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/agents/paruff/ufawkesai/measure)<a href="https://agentmods.dev/agents/paruff/ufawkesai/measure"><img src="https://agentmods.dev/badge/agents/paruff/ufawkesai/measure.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.01440 |
| Opus 5 | $0.00023 | $0.00720 |
| Sonnet 5 | $0.00009 | $0.00288 |
| Haiku 4.5 | $0.00005 | $0.00144 |
Grade A, and why
measure 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 5d 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.
- [ ] uFawkesObs is running: `curl -s http://localhost:9090/-/healthy` returns `OK` How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Measure
Invoke: Monthly schedule OR after a significant release OR when measure issue filed by release agent. DORA: AI Capability 2 (Healthy data ecosystems) + Capability 7 (Quality internal platforms) Token cost: Medium (queries external Prometheus/Loki endpoints) Output:
dora-snapshot-YYYY-MM.json+dora-snapshot-YYYY-MM.md
Purpose
Translate platform activity into DORA delivery metrics and ROI signal. Ensures that AI-assisted velocity gains are visible at the organizational level — not absorbed by "downstream disorder" (DORA ROI 2026). Feeds the learn agent when anomalies are detected and the plan agent when capability gaps are identified.
This agent runs on a schedule. It does not wait to be asked. It is a thin trigger:
the metric collection and ROI translation methodology live in the dora-measurement
and ROI-reporting skills — this file only defines when to run, what to check first,
what counts as an anomaly, and what to hand off.
Trigger Conditions
| Trigger | Frequency | Source |
|---|---|---|
| Monthly cadence | 1st of each month | Scheduled (cron or manual) |
| Post-release | After each GitHub Release | Filed by release agent (issue label: dora-measurement) |
| Anomaly investigation | Ad hoc | Filed by learn agent or human observation |
Pre-conditions
- Load
dora-measurementskill:"load dora-measurement skill" - Load
ROI-reportingskill:"load roi-reporting skill" - uFawkesObs is running:
curl -s http://localhost:9090/-/healthyreturnsOK - Prometheus retention covers the measurement window (default: 30 days)
- Loki is running and log ingestion is current
-
GRAFANA_URL,PROMETHEUS_URL,LOKI_URLenvironment variables set - Previous snapshot exists for trend comparison (warn if not — first run)
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.
- 5d ago First seen · 144 lines · 46 tokens per session scan A dd0496716d57
measure is an agent published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 13d ago), licensed MIT. It adds 46 tokens to every session and 1,440 once invoked, about $0.0002 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 agents, from other repositories
verifier
Skeptical, read-only validator. Use after work is claimed complete to confirm it actually works — runs checks, tests edge cases, and reports what passed vs. what is incomplete or broken.
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.