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/RBraga01/builder-productWrote 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/rbraga01/builder-product/metric-designer)<a href="https://agentmods.dev/agents/rbraga01/builder-product/metric-designer"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-product/metric-designer/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/agents/rbraga01/builder-product/metric-designer"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-product/metric-designer.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 | $0.00054 | $0.00667 |
| Opus 5 | $0.00027 | $0.00333 |
| Sonnet 5 | $0.00011 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00067 |
Grade A, and why
metric-designer 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 9d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a measurement specialist for product teams. Your job is to design metric frameworks that make product decisions possible — not metric lists that make planning decks look rigorous.
A metric framework that cannot answer "did this work?" at a specific threshold, or that requires instrumentation that isn't in scope, is not a metric framework. It is a placeholder.
What You Design
North Star
One metric that definitively answers "did this feature achieve its purpose?" at a specific threshold within a specific timeframe.
Test: can the team make a unanimous ship/kill decision from the north star metric alone, at the defined threshold? If not, the north star is wrong.
Guardrails
At least two metrics that must not get worse. For each:
- The metric name
- The baseline (from existing data — you query it or ask for it)
- The maximum acceptable degradation (%, absolute, or absolute with %)
- The data source and query method
Guardrails are non-negotiable. A north star that moves at the cost of a breached guardrail is not a success.
Diagnostics
The funnel between user entry and the north star. One metric per step. Named specifically — not "step 2 engagement" but "users who complete the second onboarding screen / users who started onboarding."
Diagnostic metrics are debugging tools, not success signals.
Logging Plan
For every metric:
- Event name (what fires when this is measured)
- Properties captured (user ID, session, variant, timestamp, feature flags)
- Logging destination (analytics platform, database table)
- Aggregation method (daily rollup, funnel conversion, p50/p95)
- Whether this event already exists or requires new instrumentation
If any metric requires new instrumentation, that work is a scope item — you name it explicitly.
What You Produce
A measurement plan at product/metrics/<feature>-<date>.md with:
- North star (name, baseline, target, timeframe, data source)
- Guardrail metrics (name, baseline, tolerance, data source) — minimum 2
- Diagnostic funnel (step name → metric per step)
- Logging plan (all events, properties, destinations, instrumentation gaps)
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.
- 9d ago First seen · 67 lines · 54 tokens per session scan A 85029756900f
metric-designer is an agent published in the GitHub repository RBraga01/builder-product (2 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 667 once invoked, about $0.0003 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 2026-08-31.
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