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Load workflow guide

load_skill
Read-onlyIdempotent

How this Aevia connection works, plus playbooks for results, reports, systems. Returns a skill's playbook as the result; takes no action itself. A playbook is step-by-step guidance for a multi-step job, too long for a description. connector_guide covers how this connection works: workspaces, refs, finding data, the library, building, calculating and failures. assessment_interpretation covers reading and comparing results: what an indicator result is and is not, a figure's anchors, functional-unit equivalence and comparison discipline. report_writing covers writing results up as a document, from a screening note to an ISO 14044 study. product_system_authoring covers building a new product system with lca_compose_assembly / lca_compose_linked: build order, which of the two fits, and failure modes. A loaded playbook stays in context; one load per session suffices. Skills are gated on what the token can call; an unavailable request returns the available list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_idYesId of the skill to load, e.g. `product_system_authoring`. An unknown or ungated id returns the list of skills available to this session.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish readOnly/idempotent/non-destructive/closed-world, so the description correctly focuses on what annotations cannot say: the tool takes no action, a loaded playbook persists in context, and skills are token-gated with an explicit fallback ('an unavailable request returns the available list'). That last point is valuable error-behavior disclosure, though it does not describe the playbook's size or format.

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

Conciseness4/5

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

Front-loaded with the core behavior and result semantics before the enumeration. The per-skill sentences are the value-add rather than filler, though the block is long enough that it could be tightened slightly.

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

Completeness5/5

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

With no output schema, the description carries the return-value burden and does so: it states the result is a playbook and that an unknown/gated id returns the available list. Combined with the routing detail and session guidance, nothing an agent needs to call this correctly is missing.

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 coverage is 100% so the baseline is 3, but the schema defines no enum and the description compensates by naming the concrete valid skill_ids and their subject matter. This adds real selection value beyond the schema's single generic string description.

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?

States a specific verb and resource ('Returns a skill's playbook as the result') with an explicit scope disclaimer ('takes no action itself'). The enumeration of skill_ids makes it unmistakable from siblings like knowledge_get_full_document or engine_get.

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

Usage Guidelines5/5

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

Goes well beyond 'when to use': it routes the agent to the correct skill_id by describing what each covers ('connector_guide covers how this connection works', 'assessment_interpretation covers reading and comparing results'). It also gives the operational rule 'one load per session suffices'.

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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