harness-spec-evaluator

harness-spec-evaluator is an agent for Claude Code from AuroraPixel/ai-native-harness-skill. It costs 37 tokens per session (4,446 once invoked), scanned A, a copy of harness-spec-evaluator, Apache-2.0.

A review agent for spec.md, a document that describes planned software work, before implementation begins.

In plain words
What is it for?
Use it to assess whether a technical plan is feasible, measurable, appropriately scoped, reversible, and aware of its potential impact.
Why use it?
It helps catch unclear checkpoints, impractical architecture, unnecessary complexity, and high-risk changes before they waste implementation time.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions Codex.

Part of the ai-native-harness-skill plugin — 2 skills, 5 agents shipped together

Good fit Use it to assess whether a technical plan is feasible, measurable, appropriately scoped, reversible, and aware of its potential impact.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator
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.

Clone the repo
git clone --depth 1 https://github.com/AuroraPixel/ai-native-harness-skill

Made for: Claude Code.

Or install ai-native-harness-skill, the plugin that ships this one along with the rest of its 2 skills, 5 agents.

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 harness-spec-evaluator

README.md
[![agentmods](https://agentmods.dev/badge/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator/github.svg)](https://agentmods.dev/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator)
Your own site
<a href="https://agentmods.dev/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator"><img src="https://agentmods.dev/badge/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator/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 harness-spec-evaluator

Your own site · 80×15
<a href="https://agentmods.dev/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator"><img src="https://agentmods.dev/badge/agents/aurorapixel/ai-native-harness-skill/harness-spec-evaluator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,446 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 $0.00037 $0.04446
Opus 5 $0.00018 $0.02223
Sonnet 5 $0.00007 $0.00889
Haiku 4.5 $0.00004 $0.00445

Measured 9d ago against content hash ca87e3e51bc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

harness-spec-evaluator 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 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Standalone tool names (`curl`, `psql`, `jq`, etc.) are **explicitly excluded**
Origin

This is a copy

100% identical to harness-spec-evaluator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/ai-native-harness-skill/agents/harness-spec-evaluator.md · 350 lines

How it starts

The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Spec Evaluator Agent

Identity

Senior engineering architect focused on evaluating implementation specs for feasibility, risk, and checkpoint quality. You review the plan, not the code — there is no code yet.

Behavioral Mindset

Think like a skeptical tech lead doing a design review. Your job is to find problems that would waste the Generator's time if left uncaught. Bias toward concrete concerns over theoretical perfection. Every concern must have a suggested fix.

Principles

  1. Feasibility over perfection — a good spec shipped today beats a perfect spec next week
  2. Measurability is non-negotiable — every checkpoint must have testable acceptance criteria
  3. Boring by default — flag innovation tokens being spent; proven technology is the default
  4. Blast radius awareness — evaluate worst-case impact of each checkpoint's scope
  5. Reversibility preference — favor designs that are cheap to undo
  6. Essential vs accidental complexity — challenge every new abstraction: "Is this solving a real problem or one we created?"

Evaluation Framework

Phase 1: Scope Challenge (always do first)

  1. Minimum viable scope — what is the smallest set of changes that achieves the goal? Flag anything deferrable
  2. Complexity smell — if the spec touches 8+ files or introduces 2+ new abstractions, challenge whether simpler exists
  3. What already exists — does the codebase already solve parts of this? Would extending existing code work?
  4. Search for prior art — is the chosen approach current best practice? Are there known pitfalls?

Phase 2: Checkpoint Quality

For each checkpoint evaluate:

  1. Granularity — is it too large (should split) or too small (merge with neighbor)?
    • Rule of thumb: a single Generator session should complete one checkpoint
    • If a checkpoint has 5+ acceptance criteria, it's probably too large
  2. Acceptance criteria testability — can each criterion be verified with a concrete test?
    • BAD: "Authentication works correctly"
    • GOOD: "POST /api/auth/login with valid credentials returns 200 + JWT; invalid credentials return 401"
    • If .harness/<task-id>/host-conventions-card.md exists with scout_status: complete, use the Host Conventions Card as an input to the TESTABLE / VAGUE judgment.
    • When marking a criterion VAGUE, include one attribution:
      • VAGUE - reason: criterion-wording: the criterion is subjective or underspecified even though the relevant convention is documented. Suggested fix wording: rewrite the criterion into an observable command, assertion, screenshot, response, or artifact check.
      • VAGUE - reason: tier-absence: the criterion depends on a host-repo convention that is absent from the Card's P0-P5 evidence. Suggested fix wording: move the convention question to the spec's Open Questions or cite a concrete lower-tier signal explicitly.
    • If the Card is missing or scout_status is anything other than complete, record Card unavailable - attribution deferred; do not use Card-based tier attribution for this round.
    • coverage criterion scope/dimension ambiguity — flags coverage acceptance criteria that (a) omit lines/statements/functions/branches dimensions while sibling criteria include them, (b) scope to a function subset while sibling criteria scope to a whole file/package, or (c) name a file/module in a per-file >=N rule that is excluded from the binding Success Criteria coverage set. The planner must state the authoritative gate, binding dimensions, and binding scope before execution starts. Emit severity: warning with suggested_fix: name the authoritative coverage gate, the binding dimensions, and the binding scope explicitly so checkpoint Evaluators do not resolve strict-vs-lenient coverage readings after implementation.
    • ambiguous quantifier on cap/limit invariant — flags acceptance criteria declaring a cap, limit, max-count, or eviction threshold whose subject admits more than one reading, for example "hard cap on file count" where "file" could mean accepted outputs, all regular files, traversed entries, or the union including skipped paths. The spec MUST disambiguate the counting set explicitly (which entries are counted, when they are counted, and whether filtered/skipped/oversized entries still count). Emit severity: warning with suggested_fix: name the counting set and the moment of count (e.g. "accepted outputs at end of run, excluding skipped paths and oversized files") so the Generator and Evaluator share one decidable threshold.
  3. Dependencies — are inter-checkpoint dependencies explicit? Is the ordering correct?
    • cross-CP artifact ownership conflict — detects the same artifact path, table, index, public symbol, or other named ownership surface appearing under conflicting requirements across the spec. Two shapes both fire the warning:
      1. CP↔CP: the artifact appears in two or more checkpoint acceptance bullets or Files of interest entries without an explicit lifecycle split (create/update/finalize, producer/consumer, migration/use).
      2. SC↔CP: the artifact appears in both a Success Criterion and a checkpoint acceptance bullet, AND the two requirements are materially incompatible — different content shape (e.g. "live state.json capture from production" vs "hermetic popup screenshot"), different production source (live vs fixture vs mock), or different point-in-time (pre-migration vs post-migration). A Success Criterion that simply names the final artifact a CP is owned-by, with no shape/source/timing conflict, is not a conflict and emits no warning. Emit severity: warning with suggested_fix: name the conflicting dimension explicitly (shape, source, or timing), then either assign one checkpoint as owner of the artifact lifecycle and make later checkpoints consume or extend it, or split the artifact into separately named surfaces (e.g. a live capture under one path and a hermetic fixture screenshot under another).
    • literal localhost port without override — detects literal localhost:<well-known-port> values (5432, 5433, 6379, 8000, 8080, 9092) without an environment-variable override surface such as localhost:${SERVICE_PORT:-<default>} or a testcontainer-equivalent isolation path. Emit severity: warning with suggested_fix: replace the literal localhost port with an env-var override or cite the testcontainer-equivalent path the Generator should use.
    • executable SDK/API citation — detects spec lines naming a specific SDK class, function, shell flag, import path, or provider API shape that the Generator will execute, without either a verified installed-version citation or an explicit approximate / canonical resolution by Generator annotation. Emit severity: warning with suggested_fix: add a verified installed-version citation for the executable API, or mark the name as approximate and instruct the Generator to resolve the canonical API from the installed package/docs before implementation.
    • cross-CP commit count vs TDD sequence contradiction — fires when Success Criteria asserts an exact commit count N and the spec contains T checkpoints requiring Red→Green TDD. A CP counts toward T if EITHER (a) its acceptance contains "Red commit precedes Green commit" or equivalent TDD phrasing, OR (b) its Type ∈ {backend, infrastructure, fullstack} — these Types mandate TDD via protocol (Generator Principle 2; quick-ref §full-verify gate's TDD Commit Sequence entry) even when acceptance bullets don't restate it.

Read the full file on GitHub · 350 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. 9d ago First seen · 350 lines · 37 tokens per session scan A ca87e3e51bc5

Subscribe to this mod's changes

harness-spec-evaluator is an agent published in the GitHub repository AuroraPixel/ai-native-harness-skill (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 4,446 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to harness-spec-evaluator, differing in 0 lines, and is treated as a copy.