Skip to main content
Glama
Sign In

ContentIn for Agents

by io.contentin
OverviewDiscussionsAdmin

Generate post ideas

generate_ideas

Generate fresh LinkedIn post ideas for a COLD request — the user wants options but has NOT given you material of their own ('what should I post about this week?', 'ideas for [topic]'). Ideas are grounded in the user's content pillars and their substance bank, so they are theirs rather than generic. Do NOT use this when the user has already given you their own material, a brief, or a concept in their words — that goes to write_post_in_my_voice, always. Each idea comes back with a hook and a briefing you can pass straight into write_post_in_my_voice.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "<topic>"
    },
    "name": "generate_ideas"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNoHow many ideas (1-10, default 5).
styleNoOptional. Omit to get a mix across all three styles, which is usually what the user wants.
topicYesThe topic or theme to generate ideas about.
content_pillarNoName of one of the user's content pillars that matches this topic. Omit if none fits.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false), so the bar is lower. The description still adds meaningful behavior the annotations cannot: ideas are grounded in the user's content pillars and substance bank, and each returns a hook plus a briefing passable straight into write_post_in_my_voice. It does not mention latency or limits, but none are implied by this tool.

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-loads the routing distinction and the grounding claim, and the quoted user phrasings do real disambiguation work. It is dense but nearly every clause earns its place; the closing sentence on return shape is useful for chaining rather than filler.

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?

With no output schema, the description compensates by describing what comes back (hook + briefing) and how it feeds the sibling writer tool, and it explains the data grounding. Minor gap: it never characterizes the authority/proof/growth styles, leaving their meaning to the enum labels alone.

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%, with all four parameters (including the style enum and its 'omit for a mix' default) documented in the schema itself. The description only implies the topic parameter through its quoted examples and adds no syntax or semantics beyond that, so the baseline 3 applies.

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+resource ("Generate fresh LinkedIn post ideas") and immediately scopes it to a COLD request with quoted example prompts. It explicitly distinguishes itself from write_post_in_my_voice, so an agent can route without opening either schema.

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?

Gives both the when ("user wants options but has NOT given you material of their own") and the when-not ("Do NOT use this when the user has already given you their own material, a brief, or a concept"), plus the named alternative. Nothing is left to inference.

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

All ContentIn for Agents toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources