Skip to main content
Glama
Sign In

ProductClank

by com.productclank
OverviewDiscussionsAdmin

Suggest people the audience already trusts

suggest_quote_people
Destructive

Finds people on X this brand's audience already listens to (favouring people who post clips: podcasts, interviews, talks), each checked against the live X account lookup (confirmed). Excludes people already pinned. Saves nothing — the user picks who to pin. Cost: the user's FIRST suggest is free (plan.free_suggest_available), then 50 credits per call — tell the user the cost and get a yes before a paid call. Then pass the picked handles to find_quote_moments.

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": {
      "space_id": "<space_id>"
    },
    "name": "suggest_quote_people"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicNoNarrow to a topic the audience cares about, e.g. 'B2B onboarding'.
space_idYesThe content space (brand) to run it on — from list_content_spaces. No space yet? setup_content_space first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations: exact pricing (50 credits), first-suggest-is-free logic keyed to plan.free_suggest_available, no-persistence guarantee ("Saves nothing — the user picks who to pin"), dedupe against already-pinned accounts, and live verification of each suggested account. These are precisely the facts an agent needs to inform a user and avoid an unexpected charge. The "Saves nothing" phrasing sits in mild tension with destructiveHint=true, but it reads as clarifying scope (credits spent, nothing written) rather than contradicting the annotation.

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?

Purpose is front-loaded in the first clause and every sentence carries distinct information (selection criteria, exclusions, persistence, cost, next step). It is dense — parentheticals and em-dashes pack several facts per sentence — which slightly hurts scannability for an agent parsing quickly.

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?

No output schema exists, and the description implies the return is a set of candidate people with a confirmed/verified status, which is close to sufficient. It does not explicitly say the result is a list of handles ready to hand off, but the find_quote_moments handoff makes the expected shape inferable.

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 both parameters are already fully documented in the schema, and the description does not elaborate on the topic or space_id formats. It adds selection-criteria context (clip posters preferred) but nothing about parameter behavior beyond what structured fields provide.

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 and resource ("Finds people on X this brand's audience already listens to") plus the selection bias (people who post clips) and the verification step (live X account lookup). An agent can distinguish this from find_quote_moments, which the description explicitly frames as the downstream step, and from pinning, which the user does manually.

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 explicit when-to-use routing ("Then pass the picked handles to find_quote_moments"), an exclusion rule ("Excludes people already pinned"), and a precondition gate ("tell the user the cost and get a yes before a paid call"). The space_id requirement is also linked to list_content_spaces / setup_content_space via the schema, so an agent knows the prerequisite path.

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

All ProductClank 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