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datasets_substack_search

Search stored Substack writer profiles and publications by query, handle, language, or sort to retrieve validated records from a discovery corpus; snapshots are not live.

Instructions

Search the stored Substack dataset. Searches Substack writer profiles and publications that passed public identity validation when captured. Coverage is a growing discovery corpus, not a complete directory; snapshots are not periodically revalidated and do not trigger live lookups. Inspect hydrated_at for the last successful capture.

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": "datasets_substack_search"
  }
}

Input Schema

Name	Required	Description
`q`	No	Full-text query over profile/publication name, handle, bio, host, or hero text, max 256 characters
`kind`	No	Record kind
`page`	No	Result page, 1-based
`sort`	No	Sort order: relevance, name_asc, hydrated_at_desc, hydrated_at_asc
`language`	No	Exact publication language; discover values with facet=language
`page_size`	No	Page size, default 20 and max 100
`identifier`	No	Exact public profile handle or publication host, max 253 characters

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.17.20Nov 12, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses that snapshots are not revalidated, that no live lookups occur, that coverage is partial and growing, and that freshness must be checked via hydrated_at. Missing are notes on auth, rate limits, or result-count behavior, which keeps it below a 5.

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?

Four tight sentences, front-loaded with the core action and followed by the caveats that matter. The first two sentences overlap slightly ("Search the stored Substack dataset" / "Searches Substack writer profiles and publications"), a minor redundancy rather than bloat.

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 seven-parameter search tool with no annotations and no output schema, the description covers the critical unknowns: corpus scope, staleness, absence of live lookups, and the freshness field. It does not sketch the shape of results beyond pointing at hydrated_at, but that is a modest gap given the rich schema.

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 seven parameters including both enums are already documented; the baseline of 3 applies. The description adds no parameter-level detail beyond the schema, and the one extra hint ("Inspect hydrated_at") concerns a returned field, not an input.

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 stored Substack dataset") and narrows scope to writer profiles and publications that passed public identity validation. The "stored"/"do not trigger live lookups" phrasing implicitly separates it from a live-search sibling, but no sibling is named, so differentiation relies on inference.

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?

The description makes clear this is a discovery corpus, not a complete directory, and that it will not return live data — useful exclusion context. However, it never explicitly says when to prefer this over substack_search or substack_user_search, nor routes the agent to datasets_substack_facets for language discovery; the guidance is implied rather than stated.

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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