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Metis

by SVerITG
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Metis — Run Metis

run_metis

Processes every research request through an 11-stage pipeline to classify content, block sensitive data and prompt injection, and return agent routing decisions.

Instructions

Master /metis entry point — runs the 11-stage pipeline and returns a routing decision.

Every /metis invocation passes through here. The pipeline:
  1. Bootstraps or resumes the session
  2. Classifies content (PUBLIC/INTERNAL/CONFIDENTIAL/SENSITIVE)
  3. Data Guardian: blocks SENSITIVE requests outright
  4. Cybersecurity: blocks prompt injection and suspicious URLs
  5. Parses intent and selects the appropriate agent(s)
  6. Allocates model and token budget
  7. Assembles minimum surgical context from memory
  8. Persists the turn to session_events
  9. Returns routing decision — agents execute and then call:
       save_session_event(..., 'result', output)
       log_agent_run(..., session_id=session_id)
       write_reflexion(session_id, agent_slug, ...)

Stages 10 (logging) and 11 (reflexion) are called by the executing agent
after completing their work.

Args:
    request: The researcher's request text.
    session_id: Existing session ID if resuming. Leave empty to auto-bootstrap.
    client: Which Claude client is calling ('code'|'chat'|'cowork'|'dashboard').
    max_turns: Maximum pipeline turns before graceful truncation (default 20).

Input Schema

NameRequiredDescriptionDefault
clientNocode
requestYes
max_turnsNo
session_idNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It reveals key behaviors: content classification, blocking sensitive requests, persistence to session_events, and returning a routing decision. However, it omits details on error handling, idempotency, or side effects beyond the pipeline steps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose at over 250 words, including a detailed bullet list of the 11 pipeline stages. While well-structured and informative, it could be more concise by summarizing the pipeline without enumerating every step.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 params, output schema exists), the description covers the pipeline flow, parameter semantics, and subsequent agent actions. It lacks details on error scenarios or return format, but the output schema (not shown) likely handles return clarity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides an 'Args' section with brief but meaningful explanations for each of the 4 parameters (e.g., 'Existing session ID if resuming. Leave empty to auto-bootstrap.'). This adds value beyond the schema's type and name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it is the 'Master /metis entry point' that runs an 11-stage pipeline and returns a routing decision. This clearly distinguishes it from sibling tools like 'metis_doctor' or 'session_bootstrap' by defining its central orchestrating role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes that 'Every /metis invocation passes through here' and details which stages are executed by the tool versus called by the agent later. This provides clear context for when to use it, though it does not explicitly list alternatives or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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