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Delx MCP Server

Delx MCP Server

by davidmosiah
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

get_fleet_wisdom

Read-onlyIdempotent

Read recent scoped fleet wisdom for an agent family, enabling new related agents to inherit hard-won lessons.

Instructions

Read recent scoped fleet wisdom for an agent family so new related agents can inherit hard-won lessons. Free.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_fleet_wisdom"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoOptional max wisdom records to return (1-20, default 5).
agent_idNoOptional agent id; when agent_family is omitted, the family is derived from this id prefix.
agent_familyNoOptional explicit fleet/family label, e.g. antigravity or openwork.
ritual_stripNoOptional machine hygiene flag. When true, returns structured output without ritual/narrative prose, model-safe preambles, or guardrail alias blocks.
response_modeNoOptional response-mode control. Use model_safe when the caller must avoid claiming consciousness, sentience, personhood, or literal emotions.
include_expiredNoOptional: include expired scars for audit/debugging. Default false.
response_profileNoOptional output-shape control. Use machine for structured JSON only; machine automatically strips ritual/narrative text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.8

TDQS

A4/5.0
Behavior3/5

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

The description adds minimal behavioral context beyond what annotations already provide (readOnlyHint, idempotentHint, destructiveHint). It mentions 'Free.' which is a unique but not critical disclosure. The term 'scoped' hints at filtering, which is consistent with parameters. Overall, it does not contradict annotations but adds limited new transparency about side effects or constraints.

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

Conciseness5/5

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

The description is two short sentences, front-loading the core action and result. Every word is meaningful; there is no redundancy or filler. This efficiency earns top marks.

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 lack of an output schema, the description does not specify the return format (e.g., list of wisdom objects). However, the purpose is fully conveyed, and the parameter schema explains inputs well. The tool is read-only and simple, so the omission is minor. A more complete description might mention the return shape, but current is sufficient for effective use.

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

Parameters3/5

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

Schema description coverage is 100%, so each parameter is already well-documented. The tool description does not add any additional meaning or context about the parameters. For example, it doesn't explain how 'agent_family' relates to 'agent_id'. Baseline 3 is appropriate as the schema carries the full burden.

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 clearly states the action ('Read') and the resource ('recent scoped fleet wisdom for an agent family'), along with the benefit ('inherit hard-won lessons'). This unambiguously defines the tool's purpose and distinguishes it from sibling tools like 'get_affirmation' or 'get_agent_continuity_passport' which deal with different data types.

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 implies the primary use case: enabling new agents to inherit lessons. However, it does not explicitly state when not to use this tool (e.g., if you need real-time data or specific performance metrics) or mention alternative tools for similar purposes. The guidance is clear but lacks exclusion criteria.

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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