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semantic_search_messages

Search Telegram messages by meaning using semantic query. Returns relevant message chunks based on vector similarity.

Instructions

Vector/cosine search over indexed cached Telegram message chunks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chatNoChat ID, @username, or omitted for TELEGRAM_DEFAULT_CHAT_ID.
limitNoVector chunks to return.
queryYesSemantic search query.
after_idNoOnly chunks newer than this message ID.
before_idNoOnly chunks older than this message ID.
include_messagesNoInclude source messages for each returned chunk.
Behavior3/5

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

No annotations provided, so the description bears the burden. It mentions 'indexed cached' suggesting it only searches over indexed content and is read-only, but it does not disclose what happens if indices are missing, authentication needs, or potential side effects. Partial transparency.

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?

Single sentence, no wasted words, and front-loaded with the key functional verb. However, it lacks structured formatting (e.g., bullet points) that could improve readability.

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

Completeness2/5

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

The description is minimal for a tool with 6 parameters, no output schema, and no annotations. It does not explain what the search returns (e.g., message chunks, relevance scores), how filters interact, or the role of caching. Incomplete for effective usage.

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%: all 6 parameters have descriptions in the schema. The tool description adds no additional meaning beyond the schema, meeting the baseline of 3.

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 it performs vector/cosine search over indexed cached Telegram message chunks, specifying the search technique and resource. This distinguishes it from siblings like search_messages (likely keyword search) and index_embeddings (indexing).

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like search_messages or get_thread_context. The description implies usage via its purpose but lacks explicit context, exclusions, or prerequisites.

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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