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toniher

substack-saved-mcp

by toniher

search_saved_notes

Search cached saved Substack notes by full text, author, or original note date to locate specific bookmarks offline.

Instructions

Perform full-text FTS5 search across cached saved notes.

Searches body text, author name/handle, and (for restacks) the attached post's title. query uses SQLite FTS5 syntax. Allows filtering by author (name or handle) and original note date (posted_after/posted_before, ISO 8601 strings). Substack exposes no bookmark time for notes, so saved_at is always None and saved_after/saved_before match nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
authorNo
saved_afterNo
posted_afterNo
saved_beforeNo
posted_beforeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A4.2/5.0
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 add real context: it reveals the FTS5 query syntax requirement, the exact searchable fields, and the important limitation that saved_at is always None so saved_after/saved_before are useless. It does not state read-only status or the implicit prerequisite that notes must be synced ('cached') before searching.

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?

Front-loads the core purpose in the first sentence, then layers in search scope, filter semantics, and the saved_at caveat. Every sentence adds distinct information with no redundancy or 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?

An output schema exists, so return values need not be described, and the description covers most parameters plus the FTS5 syntax requirement and the saved_at limitation. The gaps are minor: no limit/pagination semantics and no explicit read-only assurance or sync prerequisite.

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 must compensate and largely does: it defines query as FTS5 syntax, author as name-or-handle, posted_after/posted_before as ISO 8601 strings, and explicitly explains that saved_after/saved_before match nothing. Only limit is left undocumented, a minor omission given six of seven parameters are clarified.

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 ('full-text FTS5 search across cached saved notes') and further specifies exactly which fields are searched (body text, author name/handle, restack post title). The resource 'saved notes' cleanly distinguishes it from the sibling search_saved_posts, so an agent can select it without opening the schema.

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 explains capabilities and filter semantics but never says when to prefer this over list_saved_notes or search_saved_posts, nor names any alternative. It does implicitly warn against the saved_after/saved_before filters by noting they match nothing, which is useful but parameter-level rather than tool-selection guidance.

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