local-code-index
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct purpose: adding, listing, searching (single or all), and deleting repositories. No overlapping functionality.
Naming Consistency4/5Tools follow a verb_noun pattern with snake_case, though 'list_indexed_repositories' slightly deviates from the simpler 'repository' stem used by others.
Tool Count5/5With 5 tools, the set is well-scoped for a code indexing server, covering essential operations without redundancy.
Completeness4/5Core CRUD operations are present (index, list, search, delete), but an explicit update or re-index tool is missing, though index can be re-run.
Average 3.2/5 across 5 of 5 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 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 bears full responsibility for behavioral disclosure. It mentions 'verbose terminal debugging logs' which hints at output verbosity, but does not clarify if indexing is destructive, idempotent, or requires network access. Important traits like side effects or safety constraints are omitted.
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?
The description is a single sentence, highly concise and front-loaded with the main action. However, it is so brief that it sacrifices necessary details, which slightly reduces effectiveness. It earns full marks for structure but not for completeness.
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 tool's simplicity (one parameter, no nested objects) and the existence of an output schema, the description should still cover parameter semantics and usage context. The lack of parameter explanation and usage guidance makes it incomplete for an agent to use reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage (no parameter descriptions), yet the tool description does not compensate by explaining the 'repo_path' parameter. The agent is left without any guidance on what constitutes a valid path (e.g., absolute vs relative, local vs remote), making correct invocation difficult.
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 verb 'indexes' and the resource 'repository folder', making the primary action obvious. It includes an extra behavioral detail about verbose logs. However, it does not explicitly differentiate from sibling tools like 'search_codebase' or 'list_indexed_repositories' beyond the verb, but the verb itself is distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'search_codebase' or 'delete_repository'. It does not mention prerequisites, expected context, or conditions under which indexing is appropriate, leaving the agent to infer usage without support.
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?
Mentions 'high-speed' and 'global token limit' but provides no information on idempotency, side effects, authentication needs, or error behavior. With no annotations, the description fails to disclose critical behavioral traits.
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?
Extremely concise at one sentence, no filler words. However, it lacks structure such as bullet points or distinct sections that could improve readability for an AI agent.
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 three parameters with no descriptions and an output schema present, the description only provides a high-level operation name. It omits use-case context, parameter semantics, and result expectations, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not define any parameter. 'token_budget' and 'limit_per_repo' are left unexplained despite being critical for correct invocation.
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?
Uses specific verb 'executes a cross-query' and resource 'all indexed tables', clearly distinguishing it from sibling 'search_codebase' that likely targets a single repository. The scope is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'search_codebase'. The description implies it covers all indexed tables, but lacks when-not-to-use or context for selecting among siblings.
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, the description must disclose behavioral traits. It mentions 'removes completely' implying destruction, but lacks details on irreversibility, confirmation, permissions, error conditions, or side effects.
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?
The description is a single clear sentence, front-loaded with the action and identifier options. No wasted words, though it could be slightly expanded without losing conciseness.
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 presence of an output schema, the description need not explain return values. However, it lacks behavioral context for a destructive operation, such as success indication or irreversible effects. Adequate but incomplete.
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 coverage is 0%, so the description compensates by explaining that the single parameter can be either a system directory path or a database table name, adding meaning beyond the schema's string type.
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 removes a repository completely from LanceDB, specifying two identification methods (system directory path or database table name). It distinguishes from sibling tools like index_repository and search_codebase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives, nor any prerequisites or warnings. The description only states what the tool does without usage 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, the description carries the full burden. It mentions a token ceiling safeguard, hinting at a limit, but does not detail behavior when the limit is reached or confirm read-only nature. The semantic query aspect is stated but not elaborated.
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?
The description is a single sentence that is concise and front-loaded with the core action. It earns its place without unnecessary words, though more structure could improve clarity.
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?
Although an output schema exists, the description lacks context on prerequisites (e.g., the codebase must be indexed), the meaning of 'isolated', and parameter interplay. With 5 parameters, the description is too brief to be fully informative.
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 needs to compensate. However, it adds no parameter-specific details beyond the high-level purpose. The parameters repo_path, query, limit, file_filter, token_budget are not explained in the description.
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 uses specific verbs and resources, stating it performs semantic queries on code blocks from an isolated indexed codebase path with a token ceiling safeguard. This clearly differentiates it from sibling tools like search_all_codebases, which searches across all codebases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a single isolated codebase path, but does not explicitly state when to use this tool versus alternatives like search_all_codebases. No when-not-to-use guidance is provided.
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, the description carries the burden of behavioral disclosure. It notes the list includes 'active' repositories, which is useful, but lacks details on authentication, rate limits, or behavior when the database is empty.
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 a single sentence with 9 words, conveying the essential purpose without any extraneous information. It is optimally concise.
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 has no parameters and an output schema exists (which presumably documents return values), the description is nearly complete. It could optionally hint at what the output contains (e.g., repository IDs, names) but is sufficient for a simple listing 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 zero parameters, so there are no parameter semantics to add. The description does not need to compensate for schema gaps. The 100% schema coverage and absence of parameters justify a baseline of 4.
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 lists all active codebase repositories in the system database, using a specific verb and resource. It naturally distinguishes from sibling tools (delete, index, search) which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance is provided. The purpose is implied but there is no mention of when to use this tool versus search_codebase or search_all_codebases for finding specific repositories.
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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- Evaluate tool definition quality.
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