quality-targets-converge

quality-targets-converge is a skill for Claude Code from bdfinst/agentic-dev-team. It costs 119 tokens per session (5,343 once invoked), scanned A, original, MIT.

An iterative worker that improves a project's test quality against four targets: code coverage, mutation testing, repeatable results, and pre-merge speed.

In plain words
What is it for?
Use it to raise line and branch coverage, remove surviving mutants, investigate nondeterministic tests, and reduce test-suite runtime.
Why use it?
It shows which quality gap is largest, applies a small corrective action, and measures again instead of making changes without feedback.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the dev-team plugin — 98 skills, 54 agents, 4 hooks shipped together

Good fit Use it to raise line and branch coverage, remove surviving mutants, investigate nondeterministic tests, and reduce test-suite runtime.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add bdfinst/agentic-dev-team
Claude Code
/plugin install dev-team

Made for: Claude Code.

Or install dev-team, the plugin that ships this one along with the rest of its 98 skills, 54 agents, 4 hooks.

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-targets-converge

README.md
[![agentmods](https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/quality-targets-converge/github.svg)](https://agentmods.dev/skills/bdfinst/agentic-dev-team/quality-targets-converge)
Your own site
<a href="https://agentmods.dev/skills/bdfinst/agentic-dev-team/quality-targets-converge"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/quality-targets-converge/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.

agentmods 80×15 button for quality-targets-converge

Your own site · 80×15
<a href="https://agentmods.dev/skills/bdfinst/agentic-dev-team/quality-targets-converge"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/quality-targets-converge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,343 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00119 $0.05343
Opus 5.5 $0.00048 $0.02137
Sonnet 5.5 $0.00024 $0.01069
Haiku 4.5 $0.00012 $0.00534

Measured 1mo ago against content hash 2068d796fd66, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

quality-targets-converge 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 1mo 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.

plugins/dev-team/skills/quality-targets-converge/SKILL.md · 255 lines

How it starts

The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quality Targets Converge

Role: worker. The convergence close-out loop. Reads coverage, mutation, determinism, and wall-clock measurements; picks the largest gap; dispatches the smallest action that moves it; re-measures; repeats. The operator gates the loop and can waive any individual target.

You have been invoked with the /quality-targets-converge command.

Parse Arguments

Arguments: $ARGUMENTS

  • Positional: <repo-path>.
  • --parent <issue-url> — parent issue URL (or empty).
  • --repo-slug <slug> — .claude/memory/<workflow>/ namespace.
  • --workflow <name> — the workflow namespace under .claude/memory/ and .claude/plans/. Defaults to test-improve. Callers pass their own namespace so parallel runs stay quarantined.
  • --max-iterations <n> — safety cap. Default 10. The operator can extend mid-run.
  • --refactor-mode <no-refactor|refactor-allowed> — gates whether Step 4's "coverage gap, no existing seam" action may propose a paired [Refactor-for-testability] Story (see Step 4). Default refactor-allowed when the flag is absent or carries an unrecognized value — this preserves today's unconditional-propose behavior for callers other than /test-improve that don't pass the flag. Whenever the default fires because the flag was absent or unrecognized, print "refactor-mode not specified by caller — defaulting to refactor-allowed" (naming the unrecognized value received, if any) so a caller that forgot to wire the flag is visible in the run output rather than silently indistinguishable from one that explicitly wants refactor-allowed.

Path templates. Every filesystem path in the Steps below carries <workflow> as a placeholder; the skill interpolates the resolved --workflow value at run time. There is no literal workflow-name string inside a path.

Steps

1. Load targets

Read .dev-team/quality-targets.json if it exists; otherwise use defaults:

{
  "line_pct_min": 90,
  "branch_pct_min": 90,
  "surviving_mutants_max": 0,
  "determinism_runs": 5,
  "determinism_required_pass_rate": 1.0,
  "wall_clock_target_seconds": null
}

Read the full file on GitHub · 255 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. 1mo ago First seen · 255 lines · 119 tokens per session scan A 2068d796fd66

Subscribe to this mod's changes

quality-targets-converge is a skill published in the GitHub repository bdfinst/agentic-dev-team (295 stars, last pushed 4d ago), licensed MIT. It adds 119 tokens to every session and 5,343 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-03.

Related

Other skills, from other repositories

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

eval-dataset-design

A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.

bojieli/ai-agent-book · 138 tokens

tika-eval-compare

Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".

apache/tika · 50 tokens

cua-driver

Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.

davidondrej/skills · 68 tokens

jetson-validate-image

Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.

NVIDIA/skills · 50 tokens

atmos-validation

Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.

cloudposse/atmos · 31 tokens