Agent skill

Evaluating Bitrouter Routes

by bitrouter in bitrouter/bitrouter

A skill your agent uses when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely…

Apache-2.0Auto-check passedAI & LLM Engineering

Install Evaluating Bitrouter Routes

skills CLI
$ npx skills add bitrouter/bitrouter --skill evaluating-bitrouter-routes -a claude-code

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

GitHub CLI
$ gh skill install bitrouter/bitrouter evaluating-bitrouter-routes --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/bitrouter/bitrouter.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/evaluating-bitrouter-routes .claude/skills/evaluating-bitrouter-routes && 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
evaluating-bitrouter-routes
GitHub stars
235
Token cost
~1.2k tokens
SKILL.md length
557 words
Files
3 (incl. references)
Skills in repo
2
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely…

  • Works in 6 steps: Copy every decision's decision_id,… → Redact evidence before it leaves its… → List only dimensions the evaluator was… → …
  • Evaluating BitRouter route decisions
  • SKILL.md covers Classify the evaluation, Build the evaluator packet, Submit and hand off and Keep the packet consistent
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Evaluating Bitrouter Routes is an agent skill from bitrouter/bitrouter. Use when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely uncategorized evaluator sources.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/eval-exchange.md`).

It sits in AI & LLM Engineering, covering Model routing and gateways. It works with Model Context Protocol, OpenAI and Rust. The repository describes itself as: The minimal interpretable model router that learns & adapts to your agent workflows. The licence is Apache-2.0.

When your agent uses it

  • Evaluating BitRouter route decisions
  • Eval Exchange subjects with task-native verifiers
  • Human reviewers
  • Private enterprise evaluators

Example prompts

  • “/evaluating-bitrouter-routes”

Workflow steps

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

  1. Copy every decision's decision_id, policy, route_projection,
  2. Redact evidence before it leaves its private source. Retain raw messages,
  3. List only dimensions the evaluator was asked to judge. Leave unsupported
  4. Set confidence_ppm to the evaluator's confidence that its verdict is
  5. Write a draft subject with an empty evidence_digest, then seal it
  6. For a multi-decision subject, derive decision_credit from the fixed

What it can do on your machine

Read from SKILL.md and the folder at commit d6dfc24. 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 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

Evaluating Bitrouter Routes loads about 1.2k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 557 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

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 bitrouter/bitrouter at commit d6dfc24, republished under its Apache-2.0 licence (© bitrouter). 557 words, ~1,216 tokens.

Download SKILL.mdSave it as .claude/skills/evaluating-bitrouter-routes/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
evaluating-bitrouter-routes
description
Use when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely uncategorized evaluator sources.

Evaluate BitRouter Routes

Evaluate outcomes outside BitRouter's serving path. Produce an immutable result and stop after BitRouter reports its admission status. Do not run the optimizer or use low-level policy publication from the evaluator workflow.

Read the Eval Exchange reference before forming a subject or result. It is the exact current wire and authority contract.

Classify the evaluation

Choose scope from the observable outcome boundary:

Evidence boundaryScope
One request-local outcomerequest
Bounded multi-request workflow or conversationepisode
Externally defined task identity plus terminal task or verifier outcometask

Choose evaluator.kind from the actual source:

Evaluation sourceKind
Task-native verifiertask_native
Human reviewerhuman
Private enterprise evaluatorenterprise
Agentic judgeagentic
Genuinely uncategorized evaluatorgeneric

Build the evaluator packet

  1. Copy every decision's decision_id, policy, route_projection, request_key, selected_tier, baseline_tier, policy_digest, and optional experiment object from router-authored evidence. Preserve the experiment object verbatim; never invent or edit its id, arm, assignment unit, assignment-id digest, or challenger propensity.

  2. Redact evidence before it leaves its private source. Retain raw messages, tool arguments, code, and evaluator output with the evaluator; place safe, content-addressed evidence items in the subject.

  3. List only dimensions the evaluator was asked to judge. Leave unsupported dimensions absent. Use inconclusive when evidence cannot support a verdict.

  4. Set confidence_ppm to the evaluator's confidence that its verdict is correct. Use null when the evaluator or rubric does not supply confidence. For a task or episode cost result, submit the complete unit cost as cost.usd_micros with unit micro_usd; never substitute one request's price for the complete task or episode.

  5. Write a draft subject with an empty evidence_digest, then seal it:

    bash
    bro eval subject seal subject-draft.json --output subject.json
  6. For a multi-decision subject, derive decision_credit from the fixed evaluator credit policy:

    • Exact supported decision/metric mappings: emit only those mappings.
    • No policy or no exact mapping: use {} or omit the serde-defaulted field. The result remains a record but produces no per-route evidence. For a one-decision subject, empty credit means implicit full credit. When an inconclusive evaluator intentionally withholds attribution, emit that decision with weight_ppm: 0 instead. Keep hypothetical or illustrative weights outside submit-ready JSON.
Show full SKILL.md (227 more words)Show less

Submit and hand off

  1. Insert the sealed subject and submit a result that repeats its exact eval_id and evidence_digest.

    bash
    bro eval subject put subject.json --config bitrouter.yaml
    bro eval result submit result.json --config bitrouter.yaml
  2. Treat an admitted response as eligible evidence. Preserve held_out, rejected, and disputed responses as non-training records.

  3. Hand off the sealed subject, result, submission response, and private evidence references, then stop. A later bro optimize run invocation is a separate autonomous authorization; do not review, publish, or run it as part of evaluation.

Keep the packet consistent

  • Use subject seal for canonical evidence hashing and JSON.
  • Attribute metrics only to evidence-supported decisions.
  • Never copy a task- or episode-level reward onto each request. Use a fixed causal policy (for example, a matched control plus one changed route family) or withhold credit.
  • Preserve the router-authored baseline and selected tiers.
  • Preserve router-authored experiment references exactly. Optimizer membership never comes from the evaluator-owned cohort string.
  • Treat inconclusive as zero quality evidence even if an old or malformed packet assigns positive quality credit. Attribute cost or latency separately.
  • Keep evaluator identity, rubric/config digest, evidence references, confidence, and idempotency key stable for an equivalent retry.
  • Keep eval_id, result, and evidence identities attempt-specific. For task scope, keep subject_id stable for the canonical task inside its explicit run/source/policy namespace so repeated attempts cannot inflate the generic compiler's independent-task count.

© bitrouter, 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

SKILL.md and 2 other files (references) in skills/evaluating-bitrouter-routes of bitrouter/bitrouter.

  • SKILL.md
  • agents/openai.yaml
  • references/eval-exchange.md

Open the folder on GitHubat commit d6dfc24

Compare with similar skills

Evaluating Bitrouter Routes 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.

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Caching Architecturemajiayu000/litellm-rs117—~2kAutomated safety check: PassMIT
Config Architecturemajiayu000/litellm-rs117—~3.2kAutomated safety check: PassMIT
Cognee Integrations Setuptopoteretes/cognee32k—~1kAutomated safety check: NotesApache-2.0

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Questions about Evaluating Bitrouter Routes

What does Evaluating Bitrouter Routes do?

A skill your agent uses when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely…. Evaluating Bitrouter Routes is an agent skill from bitrouter/bitrouter. Use when evaluating BitRouter route decisions or Eval Exchange subjects with task-native verifiers, human reviewers, private enterprise evaluators, agentic judges, or genuinely uncategorized evaluator sources.

When should I use Evaluating Bitrouter Routes?

Evaluating Bitrouter Routes fits situations like: evaluating BitRouter route decisions; eval Exchange subjects with task-native verifiers; human reviewers; private enterprise evaluators.

How do I install Evaluating Bitrouter Routes in Claude Code?

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

How do I install Evaluating Bitrouter Routes in Codex?

Run `npx skills add bitrouter/bitrouter --skill evaluating-bitrouter-routes -a codex`. Or copy the skill folder (skills/evaluating-bitrouter-routes in bitrouter/bitrouter) into .agents/skills/evaluating-bitrouter-routes in your project. Codex loads it when a task matches its description.

Can I use Evaluating Bitrouter Routes 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 bitrouter/bitrouter --skill evaluating-bitrouter-routes -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/evaluating-bitrouter-routes, .gemini/skills/evaluating-bitrouter-routes, .github/skills/evaluating-bitrouter-routes and .opencode/skills/evaluating-bitrouter-routes in your project.

What does Evaluating Bitrouter Routes need to run?

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

Does Evaluating Bitrouter Routes 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 Evaluating Bitrouter Routes 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 Evaluating Bitrouter Routes use?

Evaluating Bitrouter Routes 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 Evaluating Bitrouter Routes use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.6k tokens, read only when the agent opens those files.

What are the alternatives to Evaluating Bitrouter Routes?

Skills that share tags, products or a category with Evaluating Bitrouter Routes: Agent Squad Python Guide (2FastLabs/agent-squad, 7.8k stars), Using Ccproxy Inspector (starbaser/ccproxy, 350 stars), Caching Architecture (majiayu000/litellm-rs, 117 stars) and Config Architecture (majiayu000/litellm-rs, 117 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Evaluating Bitrouter Routes?

bitrouter (a GitHub organization) maintains it in bitrouter/bitrouter, which has 235 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 8, 2026.

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