mcp-injector
Server Quality Checklist
Latest release: v0.3.2
- Disambiguation5/5
Each tool has a clear, distinct purpose: get_project_map provides structural overview, injector_blast_radius analyzes dependencies, injector_diagram generates sequence diagrams, injector_inspect_table inspects database schemas, injector_regex_search performs fallback searches, and injector_write_file writes files. No overlap or ambiguity.
Naming Consistency2/5Naming is inconsistent: get_project_map lacks the 'injector_' prefix used by the other five tools. The patterns after the prefix also vary: 'blast_radius' (noun phrase), 'diagram' (simple noun), 'inspect_table' (verb_noun), 'regex_search' (noun_noun), 'write_file' (verb_noun). No single convention is followed.
Tool Count5/5With 6 tools, the server covers essential operations for a code injection and analysis tool: overview, dependency analysis, visualization, database inspection, search, and file writing. The count is well-scoped and appropriate for the domain.
Completeness3/5The tool set covers reading (get_project_map), analysis (blast_radius, diagram), search (regex_search), and writing (write_file), but lacks partial file editing or incremental updates. The description emphasizes using injector_write_file for all edits, yet it only supports full file writes, leaving a notable gap for typical editing tasks.
Average 4/5 across 5 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 117 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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 present; description mentions traversing outbound dependencies but does not disclose whether the tool is read-only, has rate limits, or any 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core action, no unnecessary words.
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?
Adequate for a diagram generation tool with three parameters, but no mention of output format or return value.
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 coverage is 100%, so the description adds no extra meaning beyond what the schema already captures.
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?
Title 'injector_diagram' and description clearly state it generates a Mermaid sequence diagram for a symbol, distinct from siblings like 'get_project_map' or 'injector_blast_radius'.
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 says 'useful for visualizing architectural workflows' but lacks explicit when-to-use vs. alternatives or when-not-to-use guidance.
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?
Behavioral transparency is moderate: the description discloses the connection method and environment variable, but does not state that the operation is read-only, nor what happens on errors (e.g., table not found, connection failure). No annotations are present to supplement this.
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 extremely concise with two sentences, front-loading the main purpose and then providing necessary connection detail. No wasted words.
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 (one required parameter, no output schema), the description adequately covers the core functionality and connection requirements. It could mention what the inspection output contains, but the lack of output schema means this is not strictly necessary for basic understanding.
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 coverage is 100%, with table_name well-described in the schema. The description adds no extra meaning beyond the schema for the parameter, only providing context about the connection method (not a parameter). Thus baseline score of 3.
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?
Description clearly states it 'Inspects the live database schema of a specific table', providing a specific verb and resource. This distinguishes it from sibling tools like injector_blast_radius or injector_diagram.
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?
Description mentions the required environment variable and connection format, giving usage context. However, it does not explicitly state when to use this tool versus alternatives, nor provide exclusions or prerequisites beyond the DSN.
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?
No annotations provided, so the description must cover behavioral traits. It mentions that the tool rejects fold markers to prevent data loss, but does not disclose overwrite behavior, permissions, or error handling. Adequate but not comprehensive.
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?
Two concise sentences with no extraneous information. The critical usage directive is front-loaded.
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 write tool with two parameters and no output schema, the description provides core functionality but lacks details like overwrite behavior and error scenarios. Adequate but not fully complete.
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 coverage is 100%, and the description adds no new meaning for parameters beyond the schema's own descriptions (e.g., 'full, uncompressed source code' is already in the schema). Baseline 3 applies.
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?
Clearly states the verb 'write' and resource 'file to disk'. The description also distinguishes this tool from sibling tools (e.g., injector_diagram) by emphasizing file editing and data loss prevention.
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?
Explicitly instructs the agent to use this tool for file editing instead of native tools, citing data loss prevention. However, it does not mention when not to use or provide alternatives.
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?
No annotations provided, so description must disclose behavior. States it finds dependencies and can traverse directions, but does not mention what 'dependencies' includes (e.g., direct/transitive), performance, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, front-loaded with purpose. Every sentence adds value.
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?
Adequate for two parameters with no output schema. Covers basic behavior and direction options, but could specify return format or error handling.
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 provides 100% coverage with descriptions for both parameters. Description adds context on traversal directions but does not significantly enhance semantics beyond schema.
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?
Description uses specific verb 'finds dependencies' and resource 'specific symbol', clearly stating purpose for refactoring impact analysis. Distinguishes from siblings by specifying traversal directions.
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?
Explicitly states when to use (analyzing refactor impact) and traversal options. Lacks guidance on when not to use or alternative sibling tools.
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?
No annotations are provided, so the description must disclose behavior. It mentions bypassing FTS5 tokenization, which is a useful behavioral trait. However, it does not disclose potential performance impacts, scope of search (e.g., all files or specific directories), or whether it is read-only (inferred but not stated).
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?
Two concise sentences with no fluff. The purpose is stated first, followed by behavioral detail. Every word adds value.
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 simple search tool with two parameters and no output schema, the description covers purpose, use case, and key behavioral trait. It could mention the scope of files searched (e.g., entire project) to be fully self-contained, but overall it is sufficient.
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 coverage is 100% with clear parameter descriptions. The tool description adds minimal extra (e.g., 'punctuation-heavy strings'), but does not significantly enhance understanding beyond the schema. Baseline 3 is appropriate.
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 it is a fallback for literal or regex searches on file contents, bypassing FTS5 tokenization for punctuation-heavy strings or regex patterns. This distinguishes it from siblings, which are not search tools, and provides a specific verb-resource-modifier structure.
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 explicitly frames it as a 'fallback' and mentions when to use (for punctuation-heavy strings or regex patterns). It implies a primary FTS5 search exists but does not name alternatives, limiting explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully discloses behavior: output is compressed, read-only, and function bodies are folded. It also explains three compression tiers and the importance of not editing based on this output, which is transparent.
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 well-structured, starting with the main purpose, then detailing tiers, and ending with usage guidance. It is concise but includes necessary warnings and advice, earning a high score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description covers all essential aspects: what it does, how to use it, what the output looks like, and how it relates to other tools. It is complete for an agent to use correctly.
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 100%, so the baseline is 3. The description adds value by explaining the effect of compression tiers (e.g., 'removes comments', 'folds function bodies') and reiterating the purpose of path prefixes and unfolded files, improving clarity beyond the schema.
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 'Returns a compressed structural overview of the workspace' and details the compression tiers and intended use. It distinguishes from sibling tools by focusing on structural overview rather than other search or write operations.
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 explicitly advises when to use ('proactively to understand architecture'), warns against editing folded output, and recommends the alternative 'injector_retrieve' for full source before edits. This provides strong usage guidance.
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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