transcript-search
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one searches across transcripts, the other retrieves full session context. No overlap or ambiguity in their roles.
Naming Consistency5/5Both tools follow a consistent verb_noun pattern using snake_case: search_transcripts and get_session_context. The naming is predictable and uniform.
Tool Count4/5With only 2 tools, the set is minimal, but it is appropriately scoped for a narrow transcript search-and-retrieve workflow. Slightly on the thin side, though reasonable for the stated purpose.
Completeness5/5The workflow is complete: search for relevant transcripts and then retrieve full session context. No obvious missing operations for the domain.
Average 3.7/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'retrieve full context' without disclosing what that context includes, the return structure, pagination behavior, or any operational side effects. For a tool with no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, with the primary purpose front-loaded and the usage guidance following. There is slight redundancy between 'retrieve full context' and 'get more context from that session,' but the overall structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool, the description covers the core use case and when to call it. However, it leaves gaps: what 'full context' means, how to obtain the session_id, and what the response looks like. Acceptable but not rich enough for a tool with no annotations or output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both session_id and limit are already documented. The description adds no parameter-level detail beyond reinforcing that session_id identifies the target session, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Retrieve') and resource ('full context from a specific Claude Code session'). It also implies a distinction from the sibling tool by positioning itself as a follow-up to finding a relevant result, though it does not explicitly name the sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence explicitly tells the agent when to use this tool: after finding a relevant result, to get more context from that session. This provides clear usage context, though it does not name the alternative search tool or describe exclusion conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that matching is semantic-similarity-based and that results include matched content plus session metadata for navigation, which is meaningful beyond the tool name. It does not discuss edge cases like result truncation, but the core behavior is clearly communicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each with a distinct job: what the tool does, when to use it, and what it returns. There is no filler or redundancy, and the core action appears immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a moderately simple search tool with a fully described parameter schema, the description covers the purpose, usage context, matching mechanism, and return shape. Since there is no output schema, the mention of 'matched content with session metadata for navigation' is useful, though exact result fields are left unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all four parameters with descriptions, so the description does not need to compensate for missing parameter details. The phrase 'using semantic similarity' adds useful context that the query is a natural-language semantic query, but this is only a modest improvement over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('Search through past Claude Code session transcripts') and a distinctive method ('semantic similarity'), making the resource and behavior clear. It does not explicitly contrast with the sibling get_session_context, but the search-focused verb and scope leave little ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: 'find past discussions, solutions, or context from previous coding sessions.' It tells an agent when to use the tool, though it does not mention when not to use it or directly route to the sibling tool.
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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