YesTechie — UniFi Network & Security Integrator

Projects

list_projects

Completed YesTechie projects: real case studies from installs (warehouses, plants, offices, schools, churches, gated sites). One item returns title, summary, tags, the full write-up (typically client background and challenge, solution and equipment, results), headings, photos and videos. Use when the person wants real deployment examples / case studies. Lean list (id, slug, url, title, summary, date; page/limit/fields/detail), or one item in full with idOrSlug. (REST: GET /api/agent/v0/projects[/{idOrSlug}])

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": "list_projects"
  }
}

Input Schema

Name	Required	Description
`page`	No
`limit`	No
`detail`	No
`fields`	No	Comma-separated field names
`idOrSlug`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 22, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries full behavioral burden. It implies read-only via the GET endpoint and describes the shape of returned items (title, summary, tags, write-up, headings, photos, videos), but omits auth requirements, pagination defaults/behavior, ordering, and whether only completed projects are included.

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 what the tool returns and when to use it, then parameter modes and REST endpoint. The parenthetical list of site types is slightly verbose but adds useful scope context; no sentence is purely filler.

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

Completeness3/5

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

With no annotations and no output schema, the description must cover behavior and returns. It covers return payload fields and usage reasonably well, but leaves parameter defaults, ordering, pagination behavior, and auth unspecified — relevant gaps for an agent invoking it.

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 only 20% (only `fields` is documented in-schema). The description names page/limit/fields/detail and clarifies idOrSlug means 'one item in full,' but it does not explain the `detail` enum value ('full') or defaults for page/limit, leaving gaps the schema cannot fill.

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

Purpose4/5

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

States a specific verb and resource (completed YesTechie project case studies) and describes both lean-list and single-item modes via idOrSlug. It does not name or explicitly contrast with the sibling get_project, leaving ambiguity about which tool to use for a single project.

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?

Provides a clear usage trigger: 'Use when the person wants real deployment examples / case studies.' It does not mention when to prefer get_project over list_projects with idOrSlug, so exclusions/alternatives are implicit rather than explicit.

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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