Agent skill

Eval Cache

by closedloop-ai in closedloop-ai/claude-plugins

Check for a cached plan-evaluation.json result before launching the plan-evaluator agent.

Apache-2.0Auto-check: notes

Install Eval Cache

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/judges/skills/eval-cache .claude/skills/eval-cache && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .claude/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/judges/skills/eval-cache .agents/skills/eval-cache && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .agents/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/judges/skills/eval-cache .cursor/skills/eval-cache && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .cursor/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/closedloop-ai/claude-plugins.git --path plugins/judges/skills/eval-cache

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/judges/skills/eval-cache .gemini/skills/eval-cache && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .gemini/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/judges/skills/eval-cache .github/skills/eval-cache && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .github/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add closedloop-ai/claude-plugins --skill eval-cache -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install closedloop-ai/claude-plugins eval-cache --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/closedloop-ai/claude-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/judges/skills/eval-cache .opencode/skills/eval-cache && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "eval-cache" agent skill from https://github.com/closedloop-ai/claude-plugins/tree/main/plugins/judges/skills/eval-cache into .opencode/skills/eval-cache/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-cache", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: eval-cache
GitHub stars: 122
Token cost: ~516 tokens
SKILL.md length: 183 words
Files: 2 (incl. scripts)
Skills in repo: 41
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Check for a cached plan-evaluation.json result before launching the plan-evaluator agent.

: entering Phase 1.3
SKILL.md covers When to Use, Usage, Interpreting Output and How Freshness Works
Runs Shell scripts from its folder; calls bash
Checking simple mode

What it does

Eval Cache is an agent skill from closedloop-ai/claude-plugins. Check for a cached plan-evaluation.json result before launching the plan-evaluator agent. This skill should be used in Phase 1.3 (Simple Mode Evaluation) of the orchestrator prompt. Triggers on: entering Phase 1.3, checking simple mode, evaluating plan complexity. Returns EVALCACHEHIT with cached values or EVALCACHEMISS signaling re-evaluation is needed.

Its SKILL.md is about 520 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/check_eval_cache.sh`).

The repository describes itself as: Open-source Claude Code plugins for multi-agent software delivery. Plan-first SDLC workflow, code review, LLM quality judges, and self-learning — grounded in your codebase… The licence is Apache-2.0.

When your agent uses it

: entering Phase 1.3
Checking simple mode
Evaluating plan complexity

Example prompts

“/eval-cache”

Requirements

A Bash shell
Pre-approved tools (allowed-tools): Bash

What it can do on your machine

Read from SKILL.md and the folder at commit 476b54c. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Bash
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
- bash
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Eval Cache loads about 516 tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 183 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~93
When it runs · the whole SKILL.md, loaded when a task matches: ~516

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Bash
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from closedloop-ai/claude-plugins at commit 476b54c, republished under its Apache-2.0 licence (© closedloop-ai). 183 words, ~516 tokens.

Download SKILL.mdSave it as .claude/skills/eval-cache/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: eval-cache
description: Check for a cached plan-evaluation.json result before launching the plan-evaluator agent. This skill should be used in Phase 1.3 (Simple Mode Evaluation) of the orchestrator prompt. Triggers on: entering Phase 1.3, checking simple mode, evaluating plan complexity. Returns EVAL_CACHE_HIT with cached values or EVAL_CACHE_MISS signaling re-evaluation is needed.
allowed-tools: Bash
context: fork

Eval Cache

Check whether a prior simple-mode evaluation can be reused, avoiding a redundant plan-evaluator launch when the plan has not changed.

When to Use

Activate this skill at the start of Phase 1.3 (Simple Mode Evaluation), before launching @code:plan-evaluator. If the cache is fresh, skip the evaluator entirely and use the cached result.

Usage

Run the cache check script:

bash

bash ${CLAUDE_SKILL_DIR}/scripts/check_eval_cache.sh <WORKDIR>

Interpreting Output

The script prints one of two structured results to stdout:

Cache Hit

EVAL_CACHE_HIT
simple_mode: true|false
selected_critics: [critic1, critic2, ...]
summary: <cached evaluation summary>

Action: Parse simple_mode and selected_critics from the output. Skip launching @code:plan-evaluator and proceed with the cached values as if the evaluator had just returned them.

Cache Miss

EVAL_CACHE_MISS
reason: <why the cache is stale or missing>

Action: Launch @code:plan-evaluator as normal. The evaluator will write a fresh plan-evaluation.json that subsequent iterations can cache from.

How Freshness Works

The script uses file modification timestamps:

If plan-evaluation.json does not exist: miss
If plan.json is newer than plan-evaluation.json: miss (plan was modified since last evaluation)
If plan-evaluation.json is newer than plan.json: hit (evaluation is still valid)

This correctly handles the case where a user modifies the plan while the workflow is paused: editing plan.json updates its mtime, invalidating the cached evaluation.

Files

SKILL.md and 1 other file (scripts) in plugins/judges/skills/eval-cache of closedloop-ai/claude-plugins.

SKILL.md
scripts/check_eval_cache.sh

Open the folder on GitHubat commit 476b54c

Compare with similar skills

Eval Cache next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Eval Cache compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Eval Cache this skillclosedloop-ai/claude-plugins	122	—	~516	Automated safety check: Notes	Apache-2.0	today
Eval-Driven Development Harnessaffaan-m/ECC	275k	—	~1.5k	Automated safety check: Pass	MIT	3 days ago
Evalalirezarezvani/claude-skills	28k	1 repos	~618	Automated safety check: Pass	MIT	1 mo ago
Eval Harnessaffaan-m/ECC	275k	—	~2.2k	Automated safety check: Pass	MIT	3 days ago
Prompt Cachingdavila7/claude-code-templates	32k	6 repos	~452	Automated safety check: Pass	MIT	today
Turborepo Cachingwshobson/agents	40k	9 repos	~2k	Automated safety check: Notes	MIT	3 days ago

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More from closedloop-ai/claude-plugins

All 41 skills in this repo

Codex Review
closedloop-ai/claude-plugins
Run Codex to review a plan file and return structured feedback with a verdict.
122 GitHub stars~1.4k tokensUpdated today
Auto-check: notes
Critic Cache
closedloop-ai/claude-plugins
Check if critic reviews are still valid before re-running Phase 2.5 critics.
122 GitHub stars~528 tokensUpdated today
Auto-check: notes
Cross Repo Cache
closedloop-ai/claude-plugins
Check if cross-repo coordinator results can be reused, avoiding redundant Sonnet agent launches.
122 GitHub stars~683 tokensUpdated today
Auto-check: notes
Find Plugin File
closedloop-ai/claude-plugins
This skill should be used when needing to locate files within the Claude Code plugins cache directory (~/.claude/plugins/cache).
122 GitHub stars~812 tokensUpdated today
Auto-check passed
Gh Monitor PR
closedloop-ai/claude-plugins
Start a detached GitHub pull-request monitor that wakes the exact launching Codex Desktop or CLI root through the managed Codex App Server when review, CI, conflict, merge-queue, closure, readiness…
122 GitHub stars~5.1k tokensUpdated today
Auto-check passed
Plan Validate
closedloop-ai/claude-plugins
Deterministic plan.json validation via Python script, replacing most plan-validator agent calls.
122 GitHub stars~1.2k tokensUpdated today
Auto-check: notes

Questions about Eval Cache

What does Eval Cache do?

Check for a cached plan-evaluation.json result before launching the plan-evaluator agent. Eval Cache is an agent skill from closedloop-ai/claude-plugins.json result before launching the plan-evaluator agent.

When should I use Eval Cache?

Eval Cache fits situations like: : entering Phase 1.3; checking simple mode; evaluating plan complexity.

How do I install Eval Cache in Claude Code?

Run `npx skills add closedloop-ai/claude-plugins --skill eval-cache -a claude-code`. Or copy the skill folder (plugins/judges/skills/eval-cache in closedloop-ai/claude-plugins) into .claude/skills/eval-cache in your project. Claude Code loads it when a task matches its description.

How do I install Eval Cache in Codex?

Run `npx skills add closedloop-ai/claude-plugins --skill eval-cache -a codex`. Or copy the skill folder (plugins/judges/skills/eval-cache in closedloop-ai/claude-plugins) into .agents/skills/eval-cache in your project. Codex loads it when a task matches its description.

Can I use Eval Cache in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add closedloop-ai/claude-plugins --skill eval-cache -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eval-cache, .gemini/skills/eval-cache, .github/skills/eval-cache and .opencode/skills/eval-cache in your project.

What does Eval Cache need to run?

Going by SKILL.md and its folder, Eval Cache needs a shell for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: A Bash shell. Its frontmatter pre-approves these tools: Bash.

Does Eval Cache access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Eval Cache safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Eval Cache use?

Eval Cache is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Eval Cache use?

About 516 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Eval Cache?

Skills that share tags, products or a category with Eval Cache: Eval-Driven Development Harness (affaan-m/ECC, 275k stars), Eval (alirezarezvani/claude-skills, 28k stars), Eval Harness (affaan-m/ECC, 275k stars) and Prompt Caching (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Eval Cache?

closedloop-ai (a GitHub organization) maintains it in closedloop-ai/claude-plugins, which has 122 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on October 7, 2026.

Source: closedloop-ai/claude-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Eval Cache

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Eval Cache

When to Use

Usage

Interpreting Output

Cache Hit

Cache Miss

How Freshness Works

Files

Compare with similar skills

Similar skills

More from closedloop-ai/claude-plugins

Questions about Eval Cache