evals-specify

evals-specify is a skill for Claude Code from tikalk/adlc-team-skills. It costs 33 tokens per session (747 once invoked), scanned A, original, MIT.

A failure-analysis workflow that extracts draft pass-or-fail evaluation rules from product specifications and real AI system failures.

In plain words
What is it for?
Use it to start evaluation development, analyze production incidents, classify failure patterns, and plan test data coverage.
Why use it?
It turns observed mistakes into documented criteria and examples that can later be reviewed and used to measure quality.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to start evaluation development, analyze production incidents, classify failure patterns, and plan test data coverage.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikalk/adlc-team-skills/evals-specify
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.

Any agent
npx skills add tikalk/adlc-team-skills --skill evals-specify
Clone the repo
git clone --depth 1 https://github.com/tikalk/adlc-team-skills

Made for: Claude Code.

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 evals-specify

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-specify/github.svg)](https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-specify)
Your own site
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-specify/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 evals-specify

Your own site · 80×15
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/evals-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/evals-specify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 747 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00033 $0.00747
Opus 5 $0.00016 $0.00374
Sonnet 5 $0.00007 $0.00149
Haiku 4.5 $0.00003 $0.00075

Measured 10d ago against content hash eecbfe8fdf5c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

evals-specify 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 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/bash/setup-evals-specify.sh, scripts/powershell/setup-evals-specify.ps1), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/evals/evals-specify/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

evals-specify

What this skill does

Conducts bottom-up error analysis following EDD Principles III & IX (Error Analysis & Test Data as Code) to discover and document draft evaluation criteria from human observation of system failures.

Output:

  1. Draft Eval Records - Individual EVAL-*.md files in .adlc/drafts/evals/ with open coding notes
  2. Error Pattern Documentation - Bottom-up failure taxonomy from actual traces
  3. Pass/Fail Examples - Real examples that should pass/fail each criterion
  4. Auto-handoff to /evals-clarify for axial coding and clustering

Key EDD Principles Applied:

  • Principle III: Error Analysis & Pattern Discovery - Open coding → failure taxonomy
  • Principle IX: Test Data as Code - Dataset planning and coverage analysis
  • Principle II: Binary Pass/Fail - Maintain strict binary pass/fail conditions
  • Principle V: Trajectory Observability - Track full multi-turn conversation traces

When to use

  • Starting evaluation development: No existing criteria, need discovery from failure logs
  • Production incident analysis: Recent failures require systematic analysis
  • Quality assessment: Discovering and codifying boundary conditions from failures

When NOT to use

  • No failure traces/specs: Generate synthetic traces first, or use /evals-init to set up security baselines
  • Known criteria already exist: Use /evals-clarify to refine or /evals-implement to generate code

Process

User Input

$ARGUMENTS

Treat user input as specific failure areas or error patterns to analyze (e.g., "authentication bypass", "RAG irrelevant results").

  • --traces N — Number of traces to analyze (default: 20, min for theoretical saturation)
  • --source SOURCE — Trace source location (e.g., logs, support tickets)

Execution Steps

Phase 1: Open Coding Analysis
  • Reviews the user-provided failure logs or spec requirements.
  • Conducts open coding of traces to discover recurring failure patterns (EDD Principle III).
  • Identifies: core problem, causal conditions, and consequences.

Read the full file on GitHub · 71 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 10d ago First seen · 71 lines · 33 tokens per session scan A eecbfe8fdf5c

Subscribe to this mod's changes

evals-specify is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 747 once invoked, about $0.0002 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.