Friction

Search feedback reports

search_items

Read-onlyIdempotent

Search the free-preview feedback reports of one product, optionally by category and by words in the title or summary (all words must match). Each report carries the source threads (URL, date, quoted excerpt, state) behind it.

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": {
      "product": "<product>"
    },
    "name": "search_items"
  }
}

Input Schema

Name	Required	Description
`q`	No	Words to find in the title or summary.
`product`	Yes	Product slug, name or domain, for example grafana.
`category`	No	pain, request, workaround or switching.

Output Schema

Name	Required	Description	Default
`note`	No
`count`	Yes
`items`	Yes
`query`	Yes
`product`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered; the description adds genuinely new behavioral facts: the corpus is 'free-preview' reports, matching is conjunctive ('all words must match'), and each result carries source threads with URL, date, excerpt and state. It stops short of stating anything about result volume or ordering, but the added context is substantial beyond the annotations.

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?

Two sentences, no filler, with the scope constraint ('of one product', 'free-preview') front-loaded before the optional filters and result contents. Every clause carries information the agent needs.

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?

For a three-parameter search tool with full schema coverage, rich annotations and an output schema, the description supplies the remaining semantic pieces: matching rules and what each report contains. Only result volume, ordering, and behavior on zero matches are left unstated, which is minor given the output schema exists.

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 all three parameters including the category enum are documented in the schema, establishing the baseline of 3. The description's 'all words must match' does add conjunctive semantics beyond the schema's 'Words to find in the title or summary', which is a small but real gain over the baseline.

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 ('Search the ... feedback reports of one product') plus the optional filters, so the agent can tell it apart from a listing or per-product summary tool. It does not explicitly name the siblings (list_products, get_product_summary) as alternatives, so differentiation is implied by verb rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Optionally by category and by words' implies when the filters are appropriate, but there is no explicit when-to-use versus list_products or get_product_summary, and no exclusions or prerequisites. Usage is inferable but not spelled out.

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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