lore
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: get_context retrieves conversation context around search results, index updates the search index, list_sessions lists indexed sessions, manage_projects handles project registration, search performs searches, and status checks indexing health. The descriptions explicitly differentiate their use cases, preventing agent confusion.
Naming Consistency4/5Tool names follow a consistent snake_case pattern and use clear verbs like get, index, list, manage, search, and status. However, 'status' deviates slightly as a noun rather than a verb (e.g., 'check_status' would be more consistent), but overall the naming is predictable and readable.
Tool Count5/5With 6 tools, this server is well-scoped for its purpose of managing and searching conversation history. Each tool serves a specific function in the indexing and retrieval workflow, from setup (manage_projects, index) to query (search, get_context) and monitoring (list_sessions, status), with no unnecessary bloat.
Completeness5/5The tool set provides complete coverage for the domain of indexing and searching Claude Code sessions. It includes project management (manage_projects), indexing operations (index, status), session listing (list_sessions), search functionality (search), and context retrieval (get_context), ensuring agents can handle the full lifecycle without gaps.
Average 3.9/5 across 6 of 6 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
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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 of behavioral disclosure. It mentions that sessions are 'indexed' and implies filtering capabilities ('by project/date'), but lacks details on permissions, rate limits, pagination, or what 'indexed' entails. For a list tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior and constraints.
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?
The description is concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage. The first sentence states what it does, and the second provides context for when to use it, with no wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects like permissions or rate limits, and parameter semantics are underspecified. Without an output schema, it also doesn't describe return values (e.g., session format). For a tool with moderate complexity and no structured support, the description should provide more comprehensive guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 3 parameters with 0% description coverage, meaning no parameter details are documented in the schema. The description only vaguely references 'project/date' for filtering, which partially covers the 'project' parameter but ignores 'limit' and 'sort'. It doesn't explain what 'limit' controls (e.g., number of results) or the meaning of 'sort' enum values ('recent', 'oldest'), failing to compensate for the low schema coverage.
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 clearly states the tool's purpose: 'List all indexed Claude Code sessions.' It specifies the verb ('List') and resource ('indexed Claude Code sessions'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate this tool from sibling tools like 'search' or 'get_context', which might also involve session retrieval.
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 clear usage guidance: 'Use when the user wants to browse conversation history or find sessions by project/date.' This gives context for when to invoke the tool, such as for browsing or filtering by project/date. It doesn't explicitly state when not to use it or name alternatives like 'search', but the context is sufficient for basic decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. While it mentions the scope (across all projects), it doesn't describe what the search returns (snippets, full conversations, metadata), whether there are rate limits, authentication requirements, or how results are ordered/paginated. For a search tool with 6 parameters, this leaves significant behavioral gaps.
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?
The description is perfectly concise with two sentences that each earn their place. The first states what the tool does, and the second provides usage guidance. There's zero wasted text or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (search tool with 6 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are structured, or provide any parameter guidance. For a tool that presumably returns search results, the lack of output information is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description mentions none of the 6 parameters, not even the required 'query' parameter. While the usage context implies a search query, it doesn't explain what format the query should take, what the project/branch parameters filter, or what the date/time parameters expect.
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 clearly states the tool searches through past Claude Code conversations across all projects, which is a specific verb+resource combination. However, it doesn't explicitly distinguish this search tool from potential sibling tools like 'get_context' or 'list_sessions' that might also retrieve conversation data.
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 clear context for when to use this tool: 'when the user asks about previous discussions, past decisions, or anything from a prior conversation.' This gives good guidance but doesn't explicitly state when NOT to use it or mention alternatives among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 of behavioral disclosure. While it mentions the tool retrieves context, it lacks details on permissions, rate limits, error handling, or what the output looks like (e.g., format, size limits). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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?
The description is highly concise and front-loaded, with two sentences that directly state the purpose and usage guidelines without any wasted words. Every sentence earns its place by providing essential information efficiently.
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?
Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description covers purpose and usage well but is incomplete. It lacks details on parameters, behavioral traits, and output format, which are necessary for full understanding. The description is adequate as a minimum but has clear gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only vaguely references 'a specific search result' (implied to relate to 'chunk_id') and 'before or after a result' (implied to relate to 'direction'), but provides no specifics on parameter meanings, formats, or constraints. This fails to adequately explain the three parameters beyond basic schema hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieve more conversation context') and resource ('around a specific search result'), distinguishing it from siblings like 'search' (which finds results) or 'list_sessions' (which lists sessions). It explicitly defines the tool's scope as fetching contextual conversation snippets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Use ONLY after calling search, when you need to see what was discussed before or after a result'), including a prerequisite (must call 'search' first) and a clear use-case (viewing surrounding context). It effectively differentiates from alternatives by specifying its post-search role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 describes what the tool does (checking health/progress and showing specific metrics) but lacks details on permissions needed, rate limits, or what happens if indexing isn't running. It doesn't contradict annotations, but could be more informative.
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?
The description is appropriately sized with two sentences that are front-loaded: the first states the purpose and what it shows, the second provides usage guidance. Every sentence adds value without redundancy or waste.
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?
Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is reasonably complete. It explains the tool's purpose, what it returns, and when to use it. However, without an output schema, it could benefit from more detail on return format or error conditions, but this is minor for a status-check tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter information, but it implicitly confirms no parameters are needed by not mentioning any. This meets the baseline for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('check', 'shows') and resources ('health and progress of lore indexing', 'indexing status, session counts, DB size'). It distinguishes from siblings by focusing on monitoring rather than performing operations like 'index' or 'search'.
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 clear context for usage ('Use this to monitor indexing progress after calling index'), indicating when to use it in relation to the 'index' sibling tool. However, it doesn't explicitly state when not to use it or mention alternatives among other siblings like 'list_sessions' or 'get_context'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 explains the three discrete actions and the registration requirement, but doesn't mention permissions needed, whether changes are reversible, rate limits, or what the response looks like. For a mutation tool with zero annotation coverage, this leaves significant gaps.
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?
The description is efficiently structured with three sentences: an overview statement, specific action explanations, and a prerequisite. Every sentence adds value with no redundant information, making it easy to parse and understand.
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 2-parameter tool with no annotations and no output schema, the description provides good purpose and usage guidance but lacks details about response format, error conditions, and the exact format of the 'project' parameter. It's adequate but has clear gaps in behavioral transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains the meaning of the 'action' parameter values ('list', 'add', 'remove') and implies the 'project' parameter is used with 'add' and 'remove' actions. However, it doesn't specify what format the 'project' parameter expects (path, name, ID).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('manage', 'list', 'add', 'remove') and resources ('projects', 'indexing'), distinguishing it from sibling tools like 'index' or 'search'. It explains that this tool handles registration status for indexing, not the indexing process itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use each action ('list' to see status, 'add' to register, 'remove' to unregister) and includes a prerequisite statement ('Projects must be registered before they can be indexed') that helps differentiate from the 'index' sibling tool.
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 full burden and does well by explaining the three modes and their behaviors ('incremental' for new/changed, 'full' for delete and rebuild, 'cancel' to stop). It could mention performance impact or permissions but covers core operational traits.
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 with zero waste: first states purpose, second gives usage guidelines, third details modes. Each sentence earns its place, and the structure is front-loaded with essential information.
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 tool with 3 parameters, no annotations, and no output schema, the description is quite complete—covering purpose, usage, and key parameter semantics. It could note that 'full' mode might be resource-intensive or that 'confirm' is for safety, but it's largely adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the 'mode' parameter's three values and their meanings, which adds crucial semantics beyond the bare enum in the schema. It doesn't cover 'project' or 'confirm', but the mode explanation is substantial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Update the search index') and resources ('recent Claude Code sessions'), distinguishing it from sibling tools like 'search' or 'list_sessions' which query rather than update the index.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided on when to use this tool: 'if search returns stale results or the user asks to refresh the index.' This directly addresses the tool's purpose relative to alternatives like 'search'.
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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