Agent skill

Hermes Route

by AlexAI-MCP in AlexAI-MCP/hermes-CCC

Route Claude Code work by complexity, risk, and tool needs. An agent skill from AlexAI-MCP/hermes-CCC.

MITAuto-check passedAgent Workflows

Install Hermes Route

skills CLI
$ npx skills add AlexAI-MCP/hermes-CCC --skill hermes-route -a claude-code

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

GitHub CLI
$ gh skill install AlexAI-MCP/hermes-CCC hermes-route --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/AlexAI-MCP/hermes-CCC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hermes-route .claude/skills/hermes-route && 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
hermes-route
GitHub stars
135
Token cost
~1.9k tokens
SKILL.md length
963 words
Files
1
Skills in repo
44
Repo updated
First seen
Licence
MIT

At a glance

Route Claude Code work by complexity, risk, and tool needs. An agent skill from AlexAI-MCP/hermes-CCC.

  • Works in 10 steps: Identify the user's actual deliverable. → Decide whether the request is asking for… → Scan for hard signals → …
  • Deciding how much reasoning depth a task needs
  • SKILL.md covers Purpose, Activation Signals, Inputs To Assess and Complexity Buckets, plus 12 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Hermes Route is an agent skill from AlexAI-MCP/hermes-CCC. Route Claude Code work by complexity, risk, and tool needs. Use when deciding how much reasoning depth a task needs, whether to read project memory first, whether the task should be decomposed, and whether the work is lightweight, standard, or investigation-heavy.

Its SKILL.md is about 1.9k 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, covering Agent memory. The repository describes itself as: Hermes Agent ported to Claude Code Channel — 46 native skills, no OAuth, no external process. The licence is MIT.

When your agent uses it

  • Deciding how much reasoning depth a task needs
  • Whether to read project memory first
  • Whether the task should be decomposed
  • Whether the work is lightweight

Example prompts

  • “/hermes-route”

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Identify the user's actual deliverable.
  2. Decide whether the request is asking for implementation, review, research, or planning.
  3. Scan for hard signals
  4. Estimate the cost of taking the wrong first step.
  5. Check whether project instructions such as AGENTS.md or CLAUDE.md are likely to constrain the work.
  6. Decide whether memory should be loaded before action.
  7. Decide whether a plan is necessary.
  8. Decide whether the task can remain local or needs external verification.
  9. Decide whether the work is serial or parallelizable.
  10. Produce an execution recommendation before touching files.

What it can do on your machine

Read from SKILL.md and the folder at commit 8107e89. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    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

Hermes Route loads about 1.9k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 963 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

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 AlexAI-MCP/hermes-CCC at commit 8107e89, republished under its MIT licence (© AlexAI-MCP). 963 words, ~1,928 tokens.

Download SKILL.mdSave it as .claude/skills/hermes-route/SKILL.md (or your agent's skills folder).
name
hermes-route
description
Route Claude Code work by complexity, risk, and tool needs. Use when deciding how much reasoning depth a task needs, whether to read project memory first, whether the task should be decomposed, and whether the work is lightweight, standard, or investigation-heavy.
version
0.1.0
author
hermes-CCC (ported from Hermes Agent by NousResearch)
license
MIT
metadata.category
orchestration
metadata.ported_from
NousResearch Hermes Agent
metadata.tags
routing, planning, triage, claude-code
metadata.tools
shell, update_plan, project-docs
metadata.maturity
beta

Hermes Route

Purpose

  • Route a task before execution instead of discovering complexity halfway through.
  • Decide whether the task is lightweight, standard, or deep-investigation work.
  • Decide whether memory, docs, code search, or external research should be loaded first.
  • Decide whether the work should stay serial or be decomposed into independent streams.
  • Decide whether the task needs a short answer, a coded implementation, or a formal review.

Activation Signals

  • Use this skill when the request is ambiguous and execution strategy matters.
  • Use this skill when a task mixes coding, research, design, and review concerns.
  • Use this skill when the user asks for the "best approach" before doing work.
  • Use this skill when a repository is large and the wrong first step would waste time.
  • Use this skill when a request includes pasted code, logs, stack traces, or multiple objectives.
  • Use this skill when deciding whether model depth should be lightweight, balanced, or deep.
  • Use this skill before spawning subagents if subagent use is permitted in the environment.

Inputs To Assess

  • User goal
  • Expected deliverable
  • Repository size or scope
  • Availability of tests
  • Presence of failing output
  • Presence of URLs or external references
  • Need for exact citations or source grounding
  • Need for code edits versus explanation only
  • Need for a review mindset versus implementation mindset

Complexity Buckets

Lightweight
  • Single factual question
  • Small formatting or wording change
  • One-file trivial edit
  • Quick command lookup
  • Simple transformation with no hidden state
Standard
  • One feature or bug across a small number of files
  • Straightforward repo navigation
  • Routine API or CLI integration
  • Clear user goal with moderate context gathering
  • Normal answer length and low ambiguity
Deep
  • Bug with unclear root cause
  • Refactor with behavioral risk
  • Architecture question with tradeoffs
  • Code review over a large diff
  • Request that needs external verification
  • Request that mixes implementation, validation, and migration

Routing Procedure

  1. Identify the user's actual deliverable.
  2. Decide whether the request is asking for implementation, review, research, or planning.
  3. Scan for hard signals:
    • code blocks
    • logs
    • diffs
    • URLs
    • multiple numbered asks
    • references to bugs, regressions, or production issues
  4. Estimate the cost of taking the wrong first step.
  5. Check whether project instructions such as AGENTS.md or CLAUDE.md are likely to constrain the work.
  6. Decide whether memory should be loaded before action.
  7. Decide whether a plan is necessary.
  8. Decide whether the task can remain local or needs external verification.
  9. Decide whether the work is serial or parallelizable.
  10. Produce an execution recommendation before touching files.

Decision Rules

  • Favor lightweight when the request is self-contained and reversible.
  • Favor standard when the work is bounded but still requires code or documentation reading.
  • Favor deep when root cause, architecture, or evidence gathering dominates.
  • Favor reading memory first when the task touches existing conventions, prior decisions, or long-lived projects.
  • Favor reading project docs first when repository instructions likely govern the work.
  • Favor a review mindset when the user asks for "review", "audit", "risk", "regression", or "findings".
  • Favor implementation immediately when the task is concrete and the user did not ask to brainstorm.

Model-Depth Mapping

  • If model choice is exposed, map lightweight to a fast cheap model.
  • If model choice is exposed, map standard to the default balanced model.
  • If model choice is exposed, map deep to the strongest reasoning model.
  • If model choice is not exposed, emulate the distinction with planning depth and evidence gathering.
  • Never use a lightweight mode for debugging ambiguous failures or reviewing risky diffs.
Show full SKILL.md (394 more words)Show less

Pre-Execution Recommendations

  • Read memory first when project memory or previous decisions likely matter.
  • Read instructions first when a repo includes AGENTS.md, CLAUDE.md, or package docs.
  • Plan first when more than one workstream or nontrivial sequencing exists.
  • Implement directly when the request is bounded and the likely path is obvious.
  • Verify externally when the user asks for current information, citations, links, or latest status.

Parallelism Rules

  • Split work only when the subtasks have disjoint outputs.
  • Keep the critical path local if the next action depends on the answer.
  • Delegate sidecar research, mechanical edits, or verification only when permitted.
  • Do not delegate unclear problem framing.
  • Do not create parallel work that will race on the same files.

Warning Signs

  • The request seems simple but contains hidden integration risk.
  • The user asks for "quick" changes in security, auth, or payments code.
  • The user mixes "explain", "implement", and "review" in one sentence.
  • The task mentions "today", "latest", "current", or "most recent".
  • The task references a file, page, or document you have not read.

Output Contract

Always produce a compact routing block with:

  • Task class
  • Execution mode
  • Read first
  • Parallelism
  • Reasoning depth
  • Why
  • First concrete step

Example Output

markdown
Task class: deep
Execution mode: implement with plan
Read first: AGENTS.md, failing test output, relevant auth module
Parallelism: no
Reasoning depth: high
Why: The request is a bug fix with unclear cause and likely cross-file behavior.
First concrete step: reproduce the failure and trace the auth decision path.

Fast Heuristics

  • Code plus error output usually means deep.
  • One-file copy edit usually means lightweight.
  • Feature addition with known target files usually means standard.
  • Review requests default to deep even if no edits are required.
  • Migration requests default to deep because compatibility risks dominate.

Failure Modes

  • Overrouting a trivial task into unnecessary planning
  • Underrouting a risky task and making premature edits
  • Ignoring repo instructions that change the allowed workflow
  • Delegating work before the problem is framed
  • Treating an external-facts question as if stale local memory were enough

Recovery Moves

  • If new ambiguity appears, re-run routing instead of forcing execution.
  • If the first read reveals larger scope, upgrade from standard to deep.
  • If the task shrinks after inspection, downgrade and execute directly.
  • If the user clarifies scope, rewrite the routing block and continue.

Checklist

  1. Identify deliverable.
  2. Identify mindset: implement, review, research, or plan.
  3. Check for code, logs, URLs, and multi-part asks.
  4. Decide complexity bucket.
  5. Decide whether memory should be loaded.
  6. Decide whether instructions must be read first.
  7. Decide whether a plan is warranted.
  8. Decide whether the work can stay serial.
  9. Produce the routing block.
  10. Start the first concrete step immediately after routing.

© AlexAI-MCP, MIT. 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 skills/hermes-route of AlexAI-MCP/hermes-CCC.

Open the folder on GitHubat commit 8107e89

Compare with similar skills

Hermes Route 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.

Hermes Route compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hermes Route this skillAlexAI-MCP/hermes-CCC135—~1.9kAutomated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Compound Learning WriterEveryInc/compound-engineering-plugin25k—~2kAutomated safety check: PassMIT
Compound Learnings RefreshEveryInc/compound-engineering-plugin25k—~2kAutomated safety check: PassMIT
Ownmemgrpcer/ownmem423—~593Automated safety check: PassApache-2.0

Similar skills

  • Neat-Freak Knowledge Closeout

    KKKKhazix/khazix-skills

    Brings project docs, agent rule files, authorized memory and leftover workspace files back in line with what the code and runtime actually do at the end of a work session.

    21k GitHub stars~1.9k tokensUpdated 9 days ago
    Agent WorkflowsAuto-check passed
  • Beads Task Memory

    gastownhall/beads

    Tracks multi-session work with dependencies in the bd issue tracker so the agent can find ready tasks and recover its context after conversation compaction.

    28k GitHub stars~1.2k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Compound Learning Writer

    EveryInc/compound-engineering-plugin

    Records one solved and verified problem as a durable learning in the repository, but only when the reasoning is not already clear from the final code, tests or docs.

    25k GitHub stars~2k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Compound Learnings Refresh

    EveryInc/compound-engineering-plugin

    Audits a repo's stored learnings against the current codebase, fixes stale, overlapping or superseded docs and reports on every document.

    25k GitHub stars~2k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Ownmem

    grpcer/ownmem

    Recall this repository's OwnMem local memory before changing code, and keep it healthy.

    423 GitHub stars~593 tokensUpdated 5 days ago
    Agent WorkflowsAuto-check passed
  • Traces a factual error the user points out back to its source (a brain page, a memory file, SOUL.md or USER.md, or a hallucination) and fixes that source instead of just noting the correction.

    31k GitHub stars~3.4k tokensUpdated today
    Agent WorkflowsAuto-check passed

More from AlexAI-MCP/hermes-CCC

All 44 skills in this repo
  • GitHub Code Review

    AlexAI-MCP/hermes-CCC

    Review GitHub pull requests with a findings-first engineering mindset.

    135 GitHub stars~1.3k tokensUpdated 6 mo ago
    Auto-check passed
  • GitHub PR Workflow

    AlexAI-MCP/hermes-CCC

    Run a disciplined GitHub pull request workflow from branch creation through merge.

    135 GitHub stars~1.4k tokensUpdated 6 mo ago
    Auto-check passed
  • Hermes Memory

    AlexAI-MCP/hermes-CCC

    Manage durable project memory for Claude Code. An agent skill from AlexAI-MCP/hermes-CCC.

    135 GitHub stars~1.7k tokensUpdated 6 mo ago
    Auto-check passed
  • Hermes Skill

    AlexAI-MCP/hermes-CCC

    Create, improve, inventory, and audit Claude Code skills. An agent skill from AlexAI-MCP/hermes-CCC.

    135 GitHub stars~1.7k tokensUpdated 6 mo ago
    Auto-check passed
  • Hermes Traj

    AlexAI-MCP/hermes-CCC

    Capture Claude Code interaction trajectories in training-friendly formats.

    135 GitHub stars~1.6k tokensUpdated 6 mo ago
    Auto-check passed
  • Subagent Driven Development

    AlexAI-MCP/hermes-CCC

    Decompose Claude Code work into parallel subagent-friendly streams when the environment permits delegation.

    135 GitHub stars~1.6k tokensUpdated 6 mo ago
    Auto-check passed

Questions about Hermes Route

What does Hermes Route do?

Route Claude Code work by complexity, risk, and tool needs. An agent skill from AlexAI-MCP/hermes-CCC. Hermes Route is an agent skill from AlexAI-MCP/hermes-CCC. Route Claude Code work by complexity, risk, and tool needs.

When should I use Hermes Route?

Hermes Route fits situations like: deciding how much reasoning depth a task needs; whether to read project memory first; whether the task should be decomposed; whether the work is lightweight.

How do I install Hermes Route in Claude Code?

Run `npx skills add AlexAI-MCP/hermes-CCC --skill hermes-route -a claude-code`. Or copy the skill folder (skills/hermes-route in AlexAI-MCP/hermes-CCC) into .claude/skills/hermes-route in your project. Claude Code loads it when a task matches its description.

How do I install Hermes Route in Codex?

Run `npx skills add AlexAI-MCP/hermes-CCC --skill hermes-route -a codex`. Or copy the skill folder (skills/hermes-route in AlexAI-MCP/hermes-CCC) into .agents/skills/hermes-route in your project. Codex loads it when a task matches its description.

Can I use Hermes Route 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 AlexAI-MCP/hermes-CCC --skill hermes-route -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hermes-route, .gemini/skills/hermes-route, .github/skills/hermes-route and .opencode/skills/hermes-route in your project.

What does Hermes Route need to run?

SKILL.md names no scripts, command-line tools or credentials: Hermes Route is instructions for the agent only.

Does Hermes Route 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 Hermes Route 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 Hermes Route use?

Hermes Route is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hermes Route use?

About 1.9k tokens (SKILL.md is roughly 7.7k 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 Hermes Route?

Skills that share tags, products or a category with Hermes Route: Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Beads Task Memory (gastownhall/beads, 28k stars), Compound Learning Writer (EveryInc/compound-engineering-plugin, 25k stars) and Compound Learnings Refresh (EveryInc/compound-engineering-plugin, 25k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hermes Route?

AlexAI-MCP (a GitHub user) maintains it in AlexAI-MCP/hermes-CCC, which has 135 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on April 8, 2026.

Source: AlexAI-MCP/hermes-CCC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.