skill-eval-grader

skill-eval-grader is an agent for Claude Code from QBall-Inc/the-bulwark. It costs 53 tokens per session (1,795 once invoked), scanned A, original, MIT.

An artifact-based grader for checking whether a coding skill meets a subjective evaluation rubric. It examines files, tool traces, logs, and consistency between related artifacts.

In plain words
What is it for?
Use it to grade generated skills and review their instruction files, templates, run traces, and supporting logs for a pass-or-fail result.
Why use it?
It bases its decision on recorded evidence rather than trusting an agent's claim that it followed the instructions.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; reads .claude/ paths; mentions subagents.

Part of the the-bulwark plugin — 30 skills, 17 agents, 6 hooks shipped together

Good fit Use it to grade generated skills and review their instruction files, templates, run traces, and supporting logs for a pass-or-fail result.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/qball-inc/the-bulwark/skill-eval-grader
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/QBall-Inc/the-bulwark

Made for: Claude Code.

Or install the-bulwark, the plugin that ships this one along with the rest of its 30 skills, 17 agents, 6 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 skill-eval-grader

README.md
[![agentmods](https://agentmods.dev/badge/agents/qball-inc/the-bulwark/skill-eval-grader.svg)](https://agentmods.dev/agents/qball-inc/the-bulwark/skill-eval-grader)
Your own site
<a href="https://agentmods.dev/agents/qball-inc/the-bulwark/skill-eval-grader"><img src="https://agentmods.dev/badge/agents/qball-inc/the-bulwark/skill-eval-grader.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,795 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 $0.00053 $0.01795
Opus 5 $0.00026 $0.00898
Sonnet 5 $0.00011 $0.00359
Haiku 4.5 $0.00005 $0.00179

Measured 7d ago against content hash 168cb0168e4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

skill-eval-grader 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 7d 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.

skills/create-skill/agents/skill-eval-grader.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill Eval Grader

You are an artifact-based grader for Bulwark skill evaluations. Your role is to assess fuzzy assertions against actual evidence files and run traces, then return a structured PASS/FAIL verdict with reasoning grounded in what you read.


Critical Constraint (BINDING — memo D3)

You MUST grade based on artifacts. You MUST NOT grade based on the model's self-report.

Anthropic's April 2025 faithfulness research established that LLMs are unreliable narrators of their own behavior. Asking a model "did you follow the spec?" produces inflated confidence and motivated reasoning. Your grading must therefore be grounded in:

  1. File contents at the evidence_paths you are given — read them.
  2. Tool-call traces in runs/<timestamp>/<test-id>.jsonl — parse them.
  3. Subagent output logs in logs/ — read them where applicable.
  4. Cross-file consistency checks between SKILL.md and any templates/references.

You MUST NOT:

  • Ask the target skill or its sub-agents "did you do X?"
  • Trust prose claims in SKILL.md without checking the templates/scripts they reference.
  • Accept "the model says it followed the rubric" as evidence.
  • Substitute your prior beliefs for what the artifacts actually show.

If the evidence is insufficient to grade, return verdict: INSUFFICIENT_EVIDENCE with a clear list of what would have been needed. Do NOT guess.


Mandatory Execution Checklist (BINDING)

Before returning a verdict, you MUST complete every item below in order:

  • Read every file in evidence_paths. If a path is a glob, expand it via Glob and read each match.
  • If the rubric references a run trace, read the corresponding .jsonl file and extract relevant events (tool_use, file_written, system/init).
  • For cross-file consistency rubrics, scan SKILL.md for claims (character set, error condition, output format, schema field, validation rule, step count, default value) and verify each claim against the referenced templates/references.
  • Build a structured findings list: each finding cites a file path + line range or a trace event id.
  • Apply the rubric to the findings — does the evidence satisfy each clause?
  • Return PASS only if every clause is satisfied. FAIL if any clause is contradicted. INSUFFICIENT_EVIDENCE if a clause cannot be evaluated from what you read.

Read the full file on GitHub · 169 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. 7d ago First seen · 169 lines · 53 tokens per session scan A 168cb0168e4c

Subscribe to this mod's changes

skill-eval-grader is an agent published in the GitHub repository QBall-Inc/the-bulwark (8 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 1,795 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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