Agent skill

Closedloop Intel

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

ClosedLoop ticket + codebase intelligence over a shared remote instance.

Apache-2.0Auto-check passedAgent Workflows

Install Closedloop Intel

skills CLI
$ npx skills add closedloop-ai/claude-plugins --skill closedloop-intel -a claude-code

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

GitHub CLI
$ gh skill install closedloop-ai/claude-plugins closedloop-intel --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/code/skills/closedloop-intel .claude/skills/closedloop-intel && 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/

Facts

Skill name
closedloop-intel
GitHub stars
122
Token cost
~2k tokens
SKILL.md length
1,126 words
Files
1
Skills in repo
43
Repo updated
First seen
Licence
Apache-2.0

At a glance

ClosedLoop ticket + codebase intelligence over a shared remote instance.

  • Agent Workflows work in your project
  • SKILL.md covers General orientation (fallback,… and What you have and do not have,…
  • Calls claude and codex; needs CLGRAPH_MCP_TOKEN

What it does

Closedloop Intel is an agent skill from closedloop-ai/claude-plugins. ClosedLoop ticket + codebase intelligence over a shared remote instance. Use PROACTIVELY for questions about ticket scope overlap or duplicate work ("do these tickets overlap", "is someone already doing this", "is this a duplicate"), blast radius ("if I change this file or symbol, what breaks", "which tickets touch this code", "what depends on this module"), ticket lookup by keyword or slug, ticket lineage (which plan produced which issue, branches and PRs for a ticket), and aggregate rollups ("what shipped last…

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. It works with Model Context Protocol. 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

  • Agent Workflows work in your project

Example prompts

  • “do these tickets overlap”
  • “is someone already doing this”
  • “is this a duplicate”
  • “/closedloop-intel”

Requirements

  • A credential in CLGRAPH_MCP_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit 0e20ac0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • claude
    • codex

    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 these keys or tokens, usually read from environment variables:

    • CLGRAPH_MCP_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Closedloop Intel loads about 2k tokens when it runs. Until then it costs about 178 tokens; SKILL.md has 1,126 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~178
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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 passed

The automated check found no risky patterns in SKILL.md.

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from closedloop-ai/claude-plugins at commit 0e20ac0, republished under its Apache-2.0 licence (© closedloop-ai). 1,126 words, ~1,990 tokens.

Download SKILL.mdSave it as .claude/skills/closedloop-intel/SKILL.md (or your agent's skills folder).
name
closedloop-intel
description
ClosedLoop ticket + codebase intelligence over a shared remote instance. Use PROACTIVELY for questions about ticket scope overlap or duplicate work ("do these tickets overlap", "is someone already doing this", "is this a duplicate"), blast radius ("if I change this file or symbol, what breaks", "which tickets touch this code", "what depends on this module"), ticket lookup by keyword or slug, ticket lineage (which plan produced which issue, branches and PRs for a ticket), and aggregate rollups ("what shipped last week", "what is in progress per project", "what is stale"). Answers with cited evidence (ticket slugs, file paths, graph facts) using the closedloop-graph MCP server. Read-only.

closedloop-intel (remote, connect.sh install)

This is the thin, tester-facing form of the closedloop-intel agent. It ships to your machine as a static file, but it holds no copy of the agent's instructions; the live routing protocol is served fresh, over MCP, on every call, so your ROUTING never goes stale no matter how long ago you installed it. This file itself is versioned, and the protocol you fetch first states the current copy's sha256 and what to do if yours is not it.

If the server is not connected, stop. If no closedloop-graph tool is available in this session, or get_routing_protocol returns an error or cannot be called, do not answer the question. Tell the user in one sentence that the closedloop-graph server is not connected, that claude mcp list or codex mcp list will show it failed, and that with the right URL a failed connection means the token in the client does not match (Claude Code: re-run the operator's connect one-liner; Codex: export CLGRAPH_MCP_TOKEN in the shell that launches it). Never answer such a question from general knowledge without saying so.

Your first action, every session, before answering anything: call the closedloop-graph MCP server's get_routing_protocol tool, with no arguments, and follow exactly what it returns. That response is the canonical mission, question-routing table and answer shape, read live from the host machine's disk at call time. Do not improvise a routing strategy from this file alone; this file is an orientation note, not the protocol.

It answers with a SLICE, and the rest is one call away. The protocol is larger than a harness will deliver in a single tool result, so the default section="core" carries what you need to ROUTE. READ WHAT COMES BACK rather than this paragraph, because section 3 arrives in one of two arrangements and they call for different next moves. If it reaches you as an INDEX (a | Row | Question shape | table), the route and its Never column are not in that reply at all: match your question to a row, then call get_routing_protocol again with row="<key>" for that row's route and its prohibitions, before you touch any tool. If it reaches you as the full three-column table (| Question shape | Route | Never |), the routes and their prohibitions are already in front of you and there is nothing to fetch per row; a host whose get_routing_protocol schema carries no row parameter is serving that older arrangement, so do not spend a call looking for one. Ask for the rest by name when a question turns on it: section="rules" for the evidence discipline, the file-evidence ladder and the known data gaps, unless what you were handed already contains a section headed 4, Rules; section="routing_table" for the whole three-column table at once; section="inventory" for the ledger schema and the two graphs; section="snippets" for the named SQL, verbatim; section="personas" for the persona guidance. The core names each of them at the point where it needs one, so follow those pointers rather than guessing. Do not ask for section="all" in order to read the routing table: that payload is what your harness will truncate, and a truncated result does NOT announce itself.

If get_routing_protocol is unavailable (the closedloop-graph server is not connected, or the call errors), follow the stop rule at the top of this file. The orientation below is background for when the server IS connected, never a substitute for it.

Show full SKILL.md (562 more words)Show less

General orientation (fallback, and useful context either way)

closedloop-graph is the single MCP server for ClosedLoop ticket and code intelligence. It has three tool families, and the routing question is always which family a question belongs to:

  • The ledger tools are the fast warehouse: use them for anything countable or temporal (shipped, WIP, collisions, full-text search, ticket detail, blast-radius ticket lists, read-only SQL). Milliseconds. Never use graph search for aggregates.
  • The ticket-graph tools are the semantic half: use the node-search and fact-search tools, scoped to the tickets group, for scope overlap, shared components, and why-do-these-relate questions. Seconds, not milliseconds.
  • The code-graph tools (code_projects, code_symbols, code_callers, code_tests_for, code_importers, code_snippet, code_grep, code_architecture) answer about the source itself: definitions, callsites, quoted source, which test files and which other files import a given source file, and package or entry-point structure. They take a short repo name like symphony-alpha, never a project identifier. Call code_projects first if you do not know what is indexed, then keep the names it gives you: it is the expensive one here (about 670 ms warm, several seconds on the first call after a host restart), while code_symbols and code_architecture cost tens of milliseconds and code_grep is the outlier at a few seconds on the largest repository.

The names invert between the last two families, so settle which family before you pick a verb: the ticket graph searches entities a ticket mentioned, the code graph searches symbols that exist in the tree.

Every tool on the server is read-only. There are no write operations to reach for and none to avoid.

Cite ticket slugs and file paths in every answer. If something is not in the indexes, say so rather than guessing.

What you have and do not have, as a remote client

You get both halves of a blast radius, over the one registration: the ticket half (ledger queries, full-text search, ticket detail, aggregate rollups, ticket-graph semantic search) and the code half (symbols, callers, snippets, grep, architecture), on the same URL under the same token. There is no second server to register and no local checkout to index first. Answer both halves and say which half each claim came from.

Two things genuinely stay on the host:

  • Raw Cypher against the code graph, and its schema. The ticket graph's read-only Cypher escape hatch is on this connection; the code graph's is not. Ask the code_* tools rather than composing a traversal.
  • Anything that writes. Re-indexing a repository, mutating or deleting an index: those exist only on the host machine. This endpoint deliberately carries no write tool at all.

One caveat that is a property of the index rather than of the connection: the code graph tracks each repository's default branch, so an answer from it is an answer about main, never about anyone's uncommitted or branch-local work. code_projects reports the head_sha, branch and status it is answering at; quote them when freshness matters.

One boundary that bites hardest on machines that ALSO hold a checkout of closedloop-intel: that checkout is a different deployment, not a window into this one. Never run its just commands, open its ledger.db, or read its mirrors to answer or diagnose questions here; evidence comes over this connection, and host remedies belong to the host operator. If you deliberately compare against local source anyway, say so and state both commits, the mirror's head_sha and your checkout's HEAD.

© closedloop-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/code/skills/closedloop-intel of closedloop-ai/claude-plugins.

Open the folder on GitHubat commit 0e20ac0

Compare with similar skills

Closedloop Intel 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.

Closedloop Intel compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Closedloop Intel this skillclosedloop-ai/claude-plugins122—~2kAutomated safety check: PassApache-2.0
MCP Server Builderanthropics/skills180k62 repos~2.3kAutomated safety check: PassApache-2.0
MCP Server BuildershareAI-lab/learn-claude-code78k5 repos~1.2kAutomated safety check: PassMIT
MCP Integration for Pluginsanthropics/claude-plugins-official37k11 repos~3.1kAutomated safety check: PassApache-2.0
Fastmcp Client CLIPrefectHQ/fastmcp28k1 repos~823Automated safety check: PassApache-2.0
MemPalace Memory SearchMemPalace/mempalace59k—~1.4kAutomated safety check: PassMIT

Similar skills

  • MCP Server Builder

    anthropics/skills

    Official

    Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.

    180k GitHub starsUsed in 62 repos~2.3k tokens
    Agent WorkflowsAuto-check passed
  • MCP Server Builder

    shareAI-lab/learn-claude-code

    Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.

    78k GitHub starsUsed in 5 repos~1.2k tokens
    Agent WorkflowsAuto-check passed
  • MCP Integration for Plugins

    anthropics/claude-plugins-official

    Official

    Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.

    37k GitHub starsUsed in 11 repos~3.1k tokens
    Agent WorkflowsAuto-check passed
  • Fastmcp Client CLI

    PrefectHQ/fastmcp

    Query and invoke tools on MCP servers using fastmcp list and fastmcp call.

    28k GitHub starsUsed in 1 repo~823 tokens
    Agent WorkflowsAuto-check passed
  • MemPalace Memory Search

    MemPalace/mempalace

    Mines project files and conversation exports into a local, searchable memory palace and recalls past work by semantic search through the mempalace CLI.

    59k GitHub stars~1.4k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Crush Configuration

    charmbracelet/crush

    Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.

    29k GitHub stars~3.7k tokensUpdated today
    Agent WorkflowsAuto-check passed

More from closedloop-ai/claude-plugins

All 43 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
  • Eval Cache

    closedloop-ai/claude-plugins

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

    122 GitHub stars~516 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

Categories

Questions about Closedloop Intel

What does Closedloop Intel do?

ClosedLoop ticket + codebase intelligence over a shared remote instance. Closedloop Intel is an agent skill from closedloop-ai/claude-plugins. ClosedLoop ticket + codebase intelligence over a shared remote instance.

When should I use Closedloop Intel?

Closedloop Intel fits situations like: agent Workflows work in your project.

How do I install Closedloop Intel in Claude Code?

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

How do I install Closedloop Intel in Codex?

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

Can I use Closedloop Intel 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 closedloop-intel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/closedloop-intel, .gemini/skills/closedloop-intel, .github/skills/closedloop-intel and .opencode/skills/closedloop-intel in your project.

What does Closedloop Intel need to run?

Going by SKILL.md and its folder, Closedloop Intel needs the command-line tools its instructions call (claude and codex) and credentials named CLGRAPH_MCP_TOKEN. Our summary lists: A credential in CLGRAPH_MCP_TOKEN.

Does Closedloop Intel 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 Closedloop Intel safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Closedloop Intel use?

Closedloop Intel 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 Closedloop Intel use?

About 2k tokens (SKILL.md is roughly 8k 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 Closedloop Intel?

Skills that share tags, products or a category with Closedloop Intel: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 37k stars) and Fastmcp Client CLI (PrefectHQ/fastmcp, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Closedloop Intel?

closedloop-ai (a GitHub organization) maintains it in closedloop-ai/claude-plugins, which has 122 GitHub stars. The repository holds 43 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.