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bidclub_search_episodes

Full-text search across titles, deks, TL;DRs, digests and transcripts, with a substring sweep that handles Chinese queries the tokenizer cannot segment. Returns up to 20 metadata rows, never content. When the response carries partial: true the query only covered the newest searched_recent episodes, so say so rather than reporting an absence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesQuery text. English words are stemmed; Chinese matches as a substring.
lenNoEpisode duration bucket.
showNoShow id from bidclub_list_shows.
timeNoRestrict to episodes published within this window.
assetNoOptional asset tag ids joined by commas (equities, crypto, vc_pe, other). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.
focusNoOptional focus tag ids joined by commas (investing, company_building, technical, macro, policy). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.
personNoExact participant name, matched against the "person:" chips.
sectorNoOptional sector tag ids joined by commas (ai_software, semis, robotics, biotech, consumer, finance, blockchain, energy, space_defense). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.
source_langNoFilters by the episode's ORIGINAL language. Chinese digests exist for most English-source episodes, so do NOT set source_lang=ZH just because you want Chinese output — use the lang parameter on bidclub_get_episode instead.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / asset
      Added value: +{
      +  "description": "Optional asset tag ids joined by commas (equities, crypto, vc_pe, other). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.",
      +  "pattern": "^(?:none|(?:equities|crypto|vc_pe|other)(?:,(?:equities|crypto|vc_pe|other))*)$",
      +  "type": "string"
      +}
    • addedInput schema / properties / focus
      Added value: +{
      +  "description": "Optional focus tag ids joined by commas (investing, company_building, technical, macro, policy). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.",
      +  "pattern": "^(?:none|(?:investing|company_building|technical|macro|policy)(?:,(?:investing|company_building|technical|macro|policy))*)$",
      +  "type": "string"
      +}
    • addedInput schema / properties / sector
      Added value: +{
      +  "description": "Optional sector tag ids joined by commas (ai_software, semis, robotics, biotech, consumer, finance, blockchain, energy, space_defense). Matches any selected id within this facet and all supplied facets together. Omit for all episodes, including untagged; pass none for no episodes.",
      +  "pattern": "^(?:none|(?:ai_software|semis|robotics|biotech|consumer|finance|blockchain|energy|space_defense)(?:,(?:ai_software|semis|robotics|biotech|consumer|finance|blockchain|energy|space_defense))*)$",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers: a 20-row cap, a firm 'never content' boundary, the substring-sweep workaround for Chinese tokenization failures, and the partial: true semantics with concrete caller guidance. The partial-coverage disclosure is exactly the kind of behavioral trait an agent cannot infer from the schema, and it prevents a plausible false-negative report.

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?

Three sentences, every one load-bearing: what it searches, the result cap and content boundary, and the partial-coverage caveat. Core function is front-loaded and nothing is repeated from the schema.

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 9-parameter tool with no output schema and no annotations, the description covers the essential operational facts: search scope, row cap, content exclusion, and the partial: true failure mode. The remaining gaps are the shape of the metadata rows (no output schema to fall back on) and the undefined 'searched_recent' window behind partial coverage, but these are minor given how much the 100% schema coverage and the behavioral notes already provide.

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 the baseline of 3 applies; every parameter already carries a meaningful schema description (including the crucial source_lang warning about not setting ZH merely for Chinese output). The description's only added semantic is the 'substring sweep' mechanism behind q and Chinese handling, which lightly reinforces but does not substantively extend the schema.

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?

Description states a specific verb and resource: 'Full-text search across titles, deks, TL;DRs, digests and transcripts.' The field list and 'never content' boundary clearly distinguish it from siblings like bidclub_list_episodes (filtered listing), bidclub_get_episode (single retrieval), and bidclub_list_shows (show catalog). An agent can tell this is the search tool without opening a schema.

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

Usage Guidelines4/5

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

Context is clear: use this when you need full-text search over content-derived fields, and it warns the caller to surface partial: true coverage rather than report an absence. It also implies via 'never content' that content retrieval belongs elsewhere. However, it never explicitly names alternatives or states when not to use it versus bidclub_list_episodes, so it falls short of a 5.

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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