quality-radar

quality-radar is an agent for coding agents from tacoda/keystone. It costs 27 tokens per session (569 once invoked), scanned A, original, MIT.

A code-quality scorecard agent that combines test, lint, type-checking, security review, functional review, coverage, and complexity results. It rates five areas of a code change or whole codebase as green, yellow, or red, with cited findings.

In plain words
What is it for?
Use it to review a code diff or audit an entire codebase. It reports scores for type safety, test quality, readability, security, and functional correctness, and can propose an update to the quality state file.
Why use it?
It gives one view of quality risks that would otherwise be scattered across separate checks and review reports.

Agent

Install

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.

agentmods
npx agentmods add agents/tacoda/keystone/quality-radar
Clone the repo
git clone --depth 1 https://github.com/tacoda/keystone

Wrote 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.

agentmods badge for quality-radar

README.md
[![agentmods](https://agentmods.dev/badge/agents/tacoda/keystone/quality-radar.svg)](https://agentmods.dev/agents/tacoda/keystone/quality-radar)
Your own site
<a href="https://agentmods.dev/agents/tacoda/keystone/quality-radar"><img src="https://agentmods.dev/badge/agents/tacoda/keystone/quality-radar.svg" alt="Measured on agentmods" height="20"></a>
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 569 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00027 $0.00569
Opus 5 $0.00014 $0.00284
Sonnet 5 $0.00005 $0.00114
Haiku 4.5 $0.00003 $0.00057

Measured 3d ago against content hash e896fe8c036f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quality-radar 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 3d 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.

.charter/agents/quality-radar.md · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sensor: quality-radar

Aggregates verification and review sensors into a five-dimension scorecard for the current diff (or the whole codebase, on audit).

  • Triggeraudit (codebase-wide) and review (diff-scoped).
  • Inputs — outputs of lint, type-check, test, coverage, review-security, review-functional, plus complexity metrics from risk-fingerprint.
  • Exit condition — every dimension has a score and at least one cited finding (or an explicit "no findings").
  • Output — one score per dimension (green | yellow | red) with the citations that drove the score.
  • State writes — proposes a diff to corpus/state/quality-radar.md. User accepts or edits.

Dimensions

Dimension Driven by Green Yellow Red
Type safety type-check exit + signature churn no errors errors confined to one region errors across regions or any/unknown proliferation
Test quality test exit + coverage + test-to-code ratio in diff passes; coverage stable or up; new code tested passes; coverage flat with new code failures, coverage drop, or new code untested
Readability lint + complexity from risk-fingerprint lint clean; no new critical-complexity regions lint warns; one new high-complexity region lint errors or multiple new critical regions
Security review-security findings none low-severity only medium or higher
Performance hot-path heuristics from review-functional + diff size on perf-critical regions (flagged in CODEBASE_STATE.md) no perf-critical touch or no concerns perf-critical touch, no benchmarks perf-critical touch with regression signal

Not a gate

This is a scorecard, not a verification gate. Red on a dimension is a signal to discuss, not an automatic block — the review action decides what to do with it. The actual block is whatever the underlying sensor already imposes (a failed test blocks regardless of how the radar shades the diff).

Read the full file on GitHub · 34 lines

Changes

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.

  1. 3d ago First seen · 34 lines · 27 tokens per session scan A e896fe8c036f

Subscribe to this mod's changes

quality-radar is an agent published in the GitHub repository tacoda/keystone (44 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 569 once invoked, about $0.0001 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.

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