froggo-mission-control: Skill for Claude Code

.claude/skills/agent-evaluation/SKILL.md

agent-evaluation is a skill for Claude Code from ProfFroggo/froggo-mission-control. It costs 30 tokens per session (1,149 once invoked), scanned A, original, Apache-2.0.

Process for evaluating agent health, capability coverage, and performance — including structured reviews of soul files, task history, and skill gaps.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions CLAUDE.md.

This is ProfFroggo/froggo-mission-control's own configuration. It tells Claude Code how to work on froggo-mission-control itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything froggo-mission-control configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ProfFroggo/froggo-mission-control. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ProfFroggo/froggo-mission-control/dev/.claude/skills/agent-evaluation/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ProfFroggo/froggo-mission-control

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 agent-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/proffroggo/froggo-mission-control/agent-evaluation/github.svg)](https://agentmods.dev/skills/proffroggo/froggo-mission-control/agent-evaluation)
Your own site
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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 agent-evaluation

Your own site · 80×15
<a href="https://agentmods.dev/skills/proffroggo/froggo-mission-control/agent-evaluation"><img src="https://agentmods.dev/badge/skills/proffroggo/froggo-mission-control/agent-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,149 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 $0.00030 $0.01149
Opus 5.5 $0.00012 $0.00460
Sonnet 5.5 $0.00006 $0.00230
Haiku 4.5 $0.00003 $0.00115

Measured today against content hash 392f1ed7ecc9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agent-evaluation 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 today.

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.

.claude/skills/agent-evaluation/SKILL.md · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Evaluation

Purpose

Maintain a healthy, well-defined agent team. Catch stale definitions, identify capability gaps, surface underperforming agents, and ensure every agent has the skills and scope needed to do their job.

Trigger Conditions

Load this skill when:

  • Asked to evaluate or audit a specific agent
  • Reviewing the full agent roster for coverage gaps
  • Onboarding a new agent (to check for overlap or missing skills)
  • Reviewing agent task history for quality or performance
  • Generating an HR report on team health

Procedure

Step 1 — Load Agent Context

For each agent under review:

  1. Read their CLAUDE.md / soul file in .claude/agents/<name>.md
  2. Read their memory file at ~/mission-control/agents/<name>/MEMORY.md if it exists
  3. Check task history via mcp__mission-control-db__task_list { "assignedTo": "<agent-name>" }
  4. Note: assigned skills, role description, tool access, and output paths

Step 2 — Evaluate Definition Quality

Score each agent definition across these dimensions:

Dimension What to Check Score (1-3)
Clarity Is the role clearly defined? Can you tell what this agent does vs doesn't do?
Completeness Does it have: character, responsibilities, workflow, memory protocol, library output?
Skills Coverage Are the right skills listed? Are there obvious gaps?
Scope Boundaries Is it clear what this agent escalates vs handles solo?
Collaboration Norms Are the key collaborators named? Are handoff rules defined?

Scoring: 1 = needs revision, 2 = acceptable, 3 = strong

Step 3 — Review Task History

For the trailing 30 days:

  • How many tasks were assigned?
  • What percentage were completed vs stalled vs human-reviewed?
  • Were any tasks escalated that this agent should have handled?
  • Were tasks completed without logging activity? (anti-pattern — flag it)

Quality signals to check:

  • Task output saved to correct library path
  • Activity logged during execution (not just at end)
  • Status transitions followed the correct pipeline

Read the full file on GitHub · 132 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. today First seen · 132 lines · 30 tokens per session scan A 392f1ed7ecc9

Subscribe to this mod's changes

agent-evaluation is a skill published in the GitHub repository ProfFroggo/froggo-mission-control (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,149 once invoked, about $0.0001 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 2026-11-07.

Related

agent-evaluation compared with skills from other repositories

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