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Suggest capabilities

suggest_capabilities
Read-only

Discover what OrgLines can do for THIS user and get gentle, transparent, plan-aware suggestions. Pass 'context_hint' (the topic the user is talking about, e.g. 'клієнти/продажі' or 'expenses') to get the relevant modules; omit it for a general capability overview. Each result carries a short value line, example prompts the user could say, whether it is ACTIVE on the user's plan or LOCKED (with the package that unlocks it), and whether the user has tried it yet. Read-only, metadata ONLY (no personal content). The server enforces a frequency cap and the user's on/off preference — if it returns suppressed=true, do NOT pitch features this turn. Use this instead of guessing OrgLines' features; never invent capabilities.

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": "suggest_capabilities"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
context_hintNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond readOnlyHint/destructiveHint, it discloses that results are metadata only with no personal content, that the server enforces a frequency cap and the user's on/off preference, and that suppressed=true must halt pitching. It also explains what each result contains (value line, example prompts, ACTIVE vs LOCKED with unlocking package, tried-before flag).

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 purpose, then usage, then result shape, then the suppressed guardrail — a sensible order with no filler sentences. Some phrasing is stylistically heavy ('gentle, transparent, plan-aware') and the paragraph is dense, but each clause adds usable information.

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 compensates by enumerating what each result carries and the special suppressed=true response shape. Combined with the safety annotations and the explained context_hint, an agent has everything needed to call it correctly and interpret the output.

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 carries the burden; it does this well for context_hint by defining it as the current topic with concrete examples and stating the omit-for-overview behavior. The limit parameter is never mentioned, leaving its purpose undocumented.

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 concrete verb and resource: discover OrgLines capabilities, personalized to the current user, with plan-aware suggestions. It clearly sets itself apart from guessing/inventing features. It does not differentiate from similarly named siblings such as suggest_structure, so it falls just short of 5.

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?

Explicit conditional guidance: pass context_hint for topic-relevant modules, omit it for a general overview, and do not pitch features when suppressed=true is returned. It also says to use this instead of guessing features. The only gap is that it does not name or compare against an alternative tool.

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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