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adyoi
by adyoi

ingest_exemplar

Store a high-quality exemplar with task type, language, title, content, and outcome to enable retrieval for guiding similar LLM responses.

Instructions

Ingest a high-quality exemplar.

Input Schema

NameRequiredDescriptionDefault
titleYes
contentYes
outcomeYes
languageYes
task_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

D1.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it delivers almost nothing. 'Ingest' implies a persistent write, but there is no disclosure of what gets stored, whether duplicates are deduplicated or embedded, whether the operation is reversible, or what permissions are needed.

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

Conciseness2/5

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

It is one short sentence with no wasted words, but this is under-specification rather than conciseness — the sentence is too small to carry the definition's required information, so brevity does not earn credit here.

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

Completeness1/5

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

For a 5-parameter required-argument mutation tool with no annotations, no output schema, and no parameter descriptions, the description is completely inadequate. Nothing an agent needs in order to call this correctly is present.

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

Parameters1/5

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

All 5 required parameters (task_type, language, title, content, outcome) have 0% schema description coverage, and the description supplies no meaning for any of them. The agent cannot tell what format task_type or outcome should take, which is a critical gap for a write tool.

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

Purpose2/5

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

The description essentially restates the tool name: 'ingest_exemplar' → 'Ingest a high-quality exemplar.' The qualifier 'high-quality' adds a small amount of meaning (only quality samples should be submitted), but the description never defines what an exemplar is or how it differs from the sibling tools ingest_procedure, knowledge_ingest_text, or retrieve_exemplars.

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

Usage Guidelines2/5

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

There is no when-to-use guidance at all: no indication of when to ingest an exemplar versus ingest_procedure or the knowledge_ingest_* family, no prerequisites, and no exclusions. The agent must infer the entire usage context from the tool name.

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