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trip2g

by io.github.trip2g

federated_search

Search connected knowledge bases. Returns snippets with heading breadcrumbs (title > section > subsection) and a precise toc_path per match, same as search; results also carry an absolute kb_id (string) to use verbatim on follow-up calls. Pass kb_id for one base, kb_ids for selected bases, or omit both to fan out. Nested bases are addressed with '/': kb_id "philosophers/nietzsche" routes through the 'philosophers' peer to the base it federates (recursive), up to 3 levels deep. Canonical call: federated_search(kb_id="philosophers/", query) -> federated_note_html(kb_id="philosophers/", path=<result.note_path>) — the standard way to descend into a leaf corpus and read real content, not hub cards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kb_idNoTarget knowledge base id; nested bases use '/' (e.g. "philosophers/nietzsche" routes through the 'philosophers' peer, recursively). Federation nests up to 3 levels deep (kb_id path segments); a deeper path is rejected.
limitNoMax number of results to return (default 6)
queryYesSearch query
kb_idsNoTarget knowledge base ids; each accepts the same nested 'peer/base' form as kb_id
detail_limitNoHow many results include full snippet matches; results beyond this are returned as lightweight previews (title, path, score) to save context (default 3)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description bears the full burden of disclosing behavioral traits. It explains that returns include snippets with breadcrumbs, toc_path, and kb_id; that nesting is recursive up to 3 levels deep; and that omitting both kb_id and kb_ids fans out across all bases. The canonical call pattern further clarifies expected usage.

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?

The description is a single, well-structured paragraph. It front-loads the core purpose and efficiently covers return format, parameter usage, nesting rules, and an example. Every sentence adds value, though the density might benefit from slight reordering.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of federated search and the absence of an output schema, the description is remarkably complete. It explains return values, nesting depth limits, fan-out behavior, and provides a canonical call pattern. It addresses all key aspects needed for correct invocation.

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?

Although schema coverage is 100%, the description adds significant meaning beyond the schema by explaining the '/' nesting semantics for kb_id, the relationship between kb_id and kb_ids, and the context of detail_limit producing lightweight previews. This enhances the agent's understanding of how parameters interact.

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?

The description clearly states the verb ('search') and the resource ('connected knowledge bases'). It distinguishes this tool from its sibling 'search' by emphasizing the federated nature and providing a canonical call pattern. The return format (snippets with breadcrumbs, toc_path, kb_id) is explicitly described.

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?

The description provides explicit guidance on parameter usage: pass kb_id for one base, kb_ids for selected bases, or omit both to fan out. It explains nesting with '/' and gives a canonical call example. While it doesn't explicitly exclude scenarios (e.g., when to use plain 'search' instead), the context is clear.

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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TDQS

A3.5/5.0
Disambiguation4/5

The local/federated pairs are clearly separated by the federated_ prefix, and search, note_html, expand, and similar each have distinct roles. The main ambiguity is between instructions and wiki, which both sound like meta-instruction tools, and expand's documented leaf-reading overlap with note_html is a minor edge case.

Naming Consistency4/5

Tool names are uniformly snake_case and the federated_ prefix creates a strong, predictable pattern across local and remote counterparts. However, base names mix verbs (search, expand), nouns (instructions, wiki), a format-ish noun (note_html), and an adjective used as a command (similar), so the pattern is not fully verb_noun.

Tool Count5/5

11 tools is a well-scoped size for a read-oriented knowledge base with both local and federated access. Each tool maps to a clear workflow stage—search, read, navigate, find similar, or fetch instructions—without significant redundancy or bloat.

Completeness4/5

The tool surface covers search, reading, structural navigation, similar-note discovery, and federated equivalents, plus base instructions, which supports the core retrieval workflow end to end. The notable gap is the lack of a way to enumerate or browse all notes in a corpus without already having a query or path, though agents can work around this via search and instructions.

Resources