CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

64

Quality

81%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

68%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is lean and largely executable, with concrete YAML and CLI examples covering the core workflow. Its main weaknesses are the missing install command and the absence of validation/error-recovery steps for a batch workflow that runs multiple agents across multiple trials.

Suggestions

Add a concrete install command (e.g., the actual pip/uv/git invocation from the repository) to the Installation section instead of the current 'install from its repository' note.

Add validation and error-recovery guidance to the workflow: how to sanity-check a task YAML before batch runs, what to do when a run or judge fails (inspect the worktree, retry, interpret partial results), and how worktrees are cleaned up afterward.

Trim the 'runs on vibes' editorial sentence in the intro and the redundant worktree-isolation rationale to tighten token efficiency.

DimensionReasoningScore

Conciseness

Sections are lean with a compact metrics table and no explanations of concepts Claude already knows, but minor padding remains — the 'runs on vibes' editorializing in the intro and the rationale sentence for worktree isolation could be trimmed.

4 / 5

Actionability

Concrete, executable guidance dominates: a complete task YAML template, real CLI invocations ('agent-eval run --task ... --agent claude-code --agent aider --runs 3', 'agent-eval report --format table'), and per-judge-type YAML examples — but the Installation section gives no actual install command, only a note to 'Install agent-eval from its repository after reviewing the source.'

4 / 5

Workflow Clarity

The Define → Run → Compare sequence is clear with per-run sub-steps, but there are no validation checkpoints or error-recovery guidance (what to do when a run fails, how to verify task YAML, worktree cleanup), and this batch workflow (multiple agents × multiple runs) requires such feedback loops, capping the score at 3 per the rubric.

3 / 5

Progressive Disclosure

No bundle files exist, and the body is self-contained with clear single-level sections and only an external repository link; structure is good, though the ~138-line all-inline format leaves minor organization gains on the table.

4 / 5

Total

15

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete capabilities, explicit third-person framing, and a well-formed 'Use when' clause covering both tool selection and regression-checking scenarios. Trigger coverage is good but could add common synonyms like 'benchmark' or 'evaluate'.

DimensionReasoningScore

Specificity

The description names concrete deliverables — 'pass rate, cost, time, and consistency metrics' on 'custom tasks' with named agents (Claude Code, Aider, Codex) — but the actions center on a single comparison workflow rather than a comprehensive list of multiple concrete operations, matching anchor 4 rather than 5.

4 / 5

Completeness

It explicitly answers both what ('Head-to-head comparison of coding agents... with pass rate, cost, time, and consistency metrics') and when ('Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time') with concrete trigger phrases.

5 / 5

Trigger Term Quality

'choosing between coding agents', 'coding agents', and the named agent products are natural phrases users would say, but common synonyms like 'benchmark', 'evaluate agents', or 'agent comparison' are only partially covered via 'comparison', leaving a few natural terms missing.

4 / 5

Distinctiveness Conflict Risk

The measured agent-comparison niche is clear with distinct triggers (agent names, pass rate/cost/time metrics) and minimal risk of firing for unrelated skills.

5 / 5

Total

18

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

affaan-m/ECC

Path

skills/agent-eval/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.