Devpipe MCP Server

by drewkhoury

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but list_tasks and list_tasks_verbose overlap significantly, as both list tasks with the latter providing more detail. This could cause confusion for an agent deciding which to use. Otherwise, tools like analyze_project, create_config, and run_pipeline are clearly differentiated.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with clear verb_noun structures, such as analyze_project, create_config, and run_pipeline. There are no deviations in naming conventions, making the set predictable and easy to understand.
Tool Count5/5
With 13 tools, the count is well-scoped for a devpipe server covering configuration, execution, monitoring, and analysis. Each tool serves a specific role in the pipeline lifecycle, from setup to reporting, without feeling excessive or insufficient.
Completeness5/5
The tool set provides comprehensive coverage for devpipe operations, including configuration creation, validation, task listing, pipeline execution, and result analysis. There are no obvious gaps; it supports the full lifecycle from setup to post-run diagnostics and reporting.
Average 3.1/5 across 13 of 13 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
- Last stable release on December 8, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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 'Shows task execution statistics and averages,' which adds some context about output behavior, but it doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what happens if the config parameter is omitted. The description is insufficient for a tool with no annotation support.
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?
The description is concise with two sentences that are front-loaded: the first states the action, and the second adds output details. There is no wasted text, making it efficient, though it could be slightly more structured to improve clarity.
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?
Given the complexity of listing tasks with verbose output, no annotations, and no output schema, the description is incomplete. It lacks details on return values, error handling, or how the 'verbose' aspect differs from non-verbose alternatives. For a tool with no structured support, more context is needed to guide effective use.
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?
The input schema has 100% description coverage, with one parameter ('config') clearly documented in the schema. The description does not add any meaning beyond what the schema provides, as it doesn't explain the parameter's role or usage. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'List tasks using devpipe list --verbose command' which provides a verb ('List') and resource ('tasks'), but it's vague about what 'tasks' specifically refers to in this context. It doesn't clearly distinguish from sibling tools like 'list_tasks' (without 'verbose'), leaving ambiguity about the difference between them.
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 is provided on when to use this tool versus alternatives. It doesn't mention when to choose 'list_tasks_verbose' over 'list_tasks' or other sibling tools like 'get_dashboard_data' or 'view_run_logs', nor does it specify any prerequisites or exclusions for usage.
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. It states the tool analyzes and suggests, but doesn't describe what 'analyze' entails (e.g., file scanning, dependency parsing), potential side effects (e.g., no changes made), performance considerations (e.g., time-intensive for large directories), or output format. This is inadequate for a tool with no annotation coverage, leaving key behavioral traits unspecified.
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?
The description is a single, efficient sentence: 'Analyze project directory to detect technologies and suggest missing tasks.' It is front-loaded with the core purpose and avoids unnecessary details. However, it could be slightly more structured by separating the two outcomes (detection and suggestion) for clarity, but overall it's concise and to the point.
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?
Given the complexity of analysis tasks, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'technologies' are detected (e.g., programming languages, frameworks), how 'missing tasks' are suggested (e.g., based on best practices), or the return format. For a tool with no structured behavioral or output information, this leaves significant gaps for an AI agent to understand and use it effectively.
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?
The input schema has 100% description coverage, with the single parameter 'projectPath' documented as 'Path to project directory to analyze (defaults to current directory).' The description adds no additional meaning beyond this, such as path format requirements or validation rules. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to given the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze project directory to detect technologies and suggest missing tasks.' It specifies the verb ('analyze'), resource ('project directory'), and outcomes ('detect technologies and suggest missing tasks'). However, it doesn't explicitly distinguish this from sibling tools like 'check_devpipe' or 'validate_config', which might have overlapping analysis functions, so it doesn't reach the highest score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., use for initial project setup or periodic reviews), or exclusions (e.g., not for real-time monitoring). With many sibling tools like 'check_devpipe' and 'validate_config', the lack of differentiation leaves the agent guessing about appropriate usage scenarios.
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. It states the tool generates files but doesn't cover critical aspects: whether it overwrites existing files, requires specific permissions, has rate limits, or what the output looks like (e.g., file creation vs. content return). For a tool that likely writes configuration files, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses precise terminology ('CI/CD configuration file', 'devpipe config') and avoids redundancy. Every word earns its place, making it easy for an agent to parse quickly.
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?
Given the complexity of generating CI/CD configurations and the lack of annotations or output schema, the description is incomplete. It doesn't explain the tool's behavior (e.g., file output format, error handling), return values, or integration with siblings. For a tool with 2 parameters and no structured output, more context is needed to ensure reliable agent 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?
The input schema has 100% description coverage, with clear parameter definitions: 'config' as a path to a TOML file and 'platform' as an enum for GitHub or GitLab. The description adds no additional semantic context beyond what the schema provides, such as example usage or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate CI/CD configuration file (GitHub Actions or GitLab CI) from devpipe config.' It specifies the verb ('Generate'), resource ('CI/CD configuration file'), and source ('from devpipe config'), distinguishing it from siblings like 'create_config' or 'run_pipeline'. However, it doesn't explicitly differentiate from all siblings, such as 'generate_task', which might have overlapping functionality.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a devpipe config file), exclusions (e.g., not for other CI platforms), or compare to siblings like 'create_config' or 'validate_config'. This lack of context leaves the agent to infer usage based on the tool name alone.
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. It states the tool extracts data but doesn't specify whether this is a read-only operation, what permissions are required, how it handles missing files, or any rate limits. For a tool that likely reads files, this lack of behavioral context is a significant gap, though it doesn't contradict any annotations.
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?
The description is a single, efficient sentence that front-loads the key action ('Extract aggregated data') and specifies sources and content. There's no wasted verbiage, and it directly communicates the tool's function without redundancy. However, it could be slightly more structured by explicitly mentioning the output type or usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a simple input schema, the description is minimally adequate. It covers what data is extracted and from where, but lacks details on behavioral traits, error handling, or output format. For a tool with low complexity, this is acceptable but leaves gaps that could hinder effective agent use.
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?
The input schema has 100% description coverage, with the single parameter 'config' documented as 'Path to config.toml file to determine output directory'. The description adds no additional parameter semantics beyond this, such as default behavior if no config is provided or details on file formats. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Extract' and the resource 'aggregated data from summary.json or the HTML dashboard', specifying it includes 'overall run statistics and metrics'. This distinguishes it from siblings like 'get_last_run' or 'view_run_logs' by focusing on aggregated dashboard data rather than individual runs or logs. However, it doesn't explicitly differentiate from 'parse_metrics', which might overlap in analyzing metrics.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a prior run to have generated the dashboard files, or compare it to siblings like 'parse_etrics' or 'get_last_run'. There's no explicit when-to-use or when-not-to-use context, leaving the agent to infer usage based on the purpose alone.
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. It describes what the tool returns but lacks critical behavioral details: it doesn't specify what happens if no recent run exists (e.g., error or empty response), whether it requires specific permissions or authentication, or any rate limits. The description covers the basic operation but misses key context needed for reliable use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose and key return values. It is front-loaded with the main action ('Get results and metadata'), followed by specifics, with zero wasted words. Every part of the sentence adds value, making it appropriately concise.
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?
Given the tool's complexity (retrieving run data), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return format (e.g., structure of results/metadata), error conditions, or dependencies. For a tool that likely returns structured data about pipeline runs, more context is needed to use it effectively without trial and error.
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?
The input schema has 100% description coverage, with the single parameter 'config' documented as 'Path to config.toml file to determine output directory'. The description adds no additional parameter information beyond what the schema provides. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get results and metadata from the most recent devpipe run' with specific details about what it returns ('task results, duration, and success status'). It distinguishes itself from siblings like 'view_run_logs' by focusing on results/metadata rather than logs, and from 'list_tasks' by targeting the most recent run rather than listing tasks. However, it doesn't explicitly differentiate from all siblings (e.g., 'check_devpipe' might overlap).
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate versus 'view_run_logs' (for logs), 'list_tasks' (for task listings), or 'check_devpipe' (which might serve a similar purpose). There's also no mention of prerequisites like needing a recent run to exist. Usage is implied from the purpose but not explicitly stated.
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 full burden for behavioral disclosure. It mentions execution and returning results, but lacks critical details: whether this is a long-running process, if it requires specific permissions, potential side effects (e.g., modifying files), error handling, or performance characteristics. For a complex execution tool with 12 parameters, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with zero waste. The first sentence states the core action with key parameters, the second clarifies the execution nature and outcome. Every word earns its place without redundancy or unnecessary elaboration.
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?
For a complex execution tool with 12 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'devpipe' is, what kind of results are returned, error conditions, or execution context. The agent lacks critical information to use this tool effectively despite the comprehensive parameter schema.
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%, providing detailed documentation for all 12 parameters. The description adds minimal value beyond the schema, only vaguely referencing 'configuration and flags' without explaining parameter relationships or usage patterns. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute', 'Runs') and resource ('devpipe', 'development pipeline'), specifying it's for execution with configuration and flags. It distinguishes from siblings like 'check_devpipe' (validation) or 'list_tasks' (enumeration) by focusing on execution, though it doesn't explicitly name alternatives.
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 is provided. The description doesn't mention prerequisites, when to choose this over 'check_devpipe' for validation, or when to use 'dryRun' mode versus actual execution. It simply states what the tool does without contextual usage advice.
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. It states 'Read logs' and 'from the most recent run', implying a read-only operation focused on recent data, but it doesn't cover critical aspects like permissions needed, rate limits, pagination, error handling, or what the logs contain (e.g., format, verbosity). This leaves significant gaps for an agent to understand how to interact with the tool effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Read logs') and scope ('from a specific task or the entire pipeline from the most recent run'). There is no wasted text, and it directly communicates the essential information without redundancy or unnecessary elaboration.
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?
Given the complexity of log retrieval (which can involve permissions, data formats, and error cases), no annotations, and no output schema, the description is insufficient. It lacks details on what the logs contain, how they're structured, potential errors, or dependencies on other tools like 'get_last_run'. For a tool with two parameters and behavioral nuances, this minimal description doesn't provide enough context for reliable agent use.
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%, with clear descriptions for both parameters: 'taskId' specifies it's for viewing logs for a task or defaults to pipeline.log, and 'config' indicates it determines the output directory. The description adds marginal value by implying the scope ('specific task or entire pipeline') but doesn't provide additional syntax, format details, or examples beyond what the schema already documents, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Read logs') and resource ('from a specific task or the entire pipeline'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from potential sibling tools like 'get_last_run' or 'parse_metrics', which might also involve run-related data, leaving some ambiguity about its unique role.
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?
The description provides minimal guidance by mentioning 'from a specific task or the entire pipeline', but it doesn't specify when to use this tool versus alternatives like 'get_last_run' (which might provide run status) or 'parse_metrics' (which could handle log analysis). No explicit when-not-to-use or prerequisite information is included, limiting its utility for 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks installation status and retrieves version info, but doesn't describe how it performs the check (e.g., local command execution, API call), what happens if devpipe is not installed (e.g., returns error or null), or any side effects like network calls or permissions needed. This leaves significant gaps for a tool that likely interacts with external systems.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Check if devpipe is installed and get version information.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple diagnostic tool. Every part of the sentence contributes directly to understanding the tool's function.
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?
Given the tool's likely complexity (checking external installation and versioning) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., version string, boolean status, error messages), how it handles failures, or any dependencies. For a tool that interacts with an external component like devpipe, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). With no parameters, the description doesn't need to add semantic details beyond what the schema provides. The baseline for 0 parameters is 4, as the description adequately covers the tool's intent without parameter-related gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check if devpipe is installed and get version information.' It specifies the verb ('check') and resource ('devpipe') with the additional action of retrieving version information. However, it doesn't explicitly differentiate this from sibling tools like 'validate_config' or 'run_pipeline' that might also interact with devpipe in different ways.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether devpipe needs to be accessible), exclusions, or suggest sibling tools for related tasks like 'run_pipeline' for execution or 'validate_config' for configuration checks. Usage is implied only by the purpose statement.
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. It states the tool generates configuration but doesn't clarify whether this is a read-only operation, if it modifies existing data, what permissions are required, or what the output format looks like. For a configuration generation tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
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?
The description is appropriately sized with two sentences that are front-loaded with the core purpose. The second sentence adds specific usage guidance without redundancy. It avoids unnecessary elaboration, though it could be slightly more structured for clarity.
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?
Given the tool has no annotations and no output schema, the description is incomplete. It doesn't explain what the generated configuration looks like, how it's returned, or any behavioral traits like error handling. For a tool that presumably outputs structured data, this lack of context makes it inadequate for full understanding.
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%, so the schema already documents all three parameters thoroughly. The description adds minimal value by hinting at the 'technology="phase"' use case, but doesn't provide additional syntax, format details, or examples beyond what the schema specifies. This meets the baseline for high schema coverage without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate task configuration from template') and specifies the resource ('for a specific technology and task type'), making the purpose understandable. It distinguishes itself from siblings like 'create_config' or 'generate_ci_config' by focusing on task-level configuration rather than broader project or CI setup. However, it doesn't explicitly differentiate from 'list_tasks' or 'run_pipeline', leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by mentioning 'Use technology="phase" to create phase headers,' which suggests a specific scenario for this parameter value. However, it lacks explicit when-to-use instructions compared to alternatives like 'create_config' or 'generate_ci_config', and doesn't mention prerequisites or exclusions. The guidance is helpful but incomplete for full context.
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. It states the tool validates for 'syntax and structure errors,' which implies a read-only, non-destructive operation, but doesn't confirm this explicitly. It lacks details on permissions, rate limits, output format, or error handling, leaving gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses clear language and avoids redundancy, making it easy to parse quickly. Every word earns its place, adhering to best practices for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (validation of config files), lack of annotations, and no output schema, the description is minimally adequate. It covers what the tool does but misses behavioral context and usage guidance. For a tool with no structured safety or output information, it should provide more completeness, such as explaining return values or error conditions.
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?
The input schema has 100% description coverage, with the 'configs' parameter fully documented in the schema. The description adds minimal value beyond the schema, as it doesn't elaborate on parameter usage, constraints, or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate with additional semantic insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validate one or more devpipe config.toml files for syntax and structure errors.' It specifies the verb (validate), resource (devpipe config.toml files), and scope (syntax and structure errors). However, it doesn't explicitly differentiate from sibling tools like 'check_devpipe' or 'analyze_project', which might have overlapping validation functions.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'check_devpipe' or 'analyze_project', nor does it specify prerequisites, exclusions, or contextual cues for selection. The agent must infer usage based on the tool name and description alone.
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. It mentions parsing and analyzing metrics, which implies a read-only operation, but doesn't specify whether it requires authentication, has rate limits, or what the output looks like (e.g., structured data or summary). For a tool with no annotations, this leaves significant gaps in understanding its 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action ('parse') and context ('devpipe run'), with no wasted words. It directly states the purpose and supported formats, making it easy for an agent to quickly grasp the tool's function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and formats, but lacks details on output behavior, error handling, or integration with sibling tools. Without annotations or output schema, the agent might struggle to fully understand how to use this tool effectively in context.
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?
The input schema has 100% description coverage, clearly documenting both parameters (metricsPath and format with enum values). The description adds minimal value beyond the schema by mentioning the file types (JUnit XML or SARIF JSON) and the context of 'devpipe run', but doesn't provide additional syntax, format details, or usage examples. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: parsing metrics from devpipe runs to analyze test results or security findings. It specifies the verb 'parse' and the resource 'metrics', and mentions the source formats (JUnit XML or SARIF JSON). However, it doesn't explicitly differentiate from sibling tools like 'get_dashboard_data' or 'view_run_logs', which might also handle devpipe data, so it doesn't reach the highest clarity level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'devpipe run' and the specific formats (JUnit or SARIF), suggesting it should be used when analyzing test or security metrics from such runs. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_last_run' or 'analyze_project', nor does it state any exclusions or prerequisites, leaving some ambiguity for the agent.
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 full burden. It mentions 'auto-detected tasks based on project technologies' but doesn't disclose behavioral traits like what happens if the file already exists, whether this is a destructive operation, what permissions are needed, or what the output format looks like. The description is insufficient for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Create a complete config.toml file from scratch') and adds essential context ('with auto-detected tasks based on project technologies'). Every word earns its place with zero waste.
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?
For a mutation tool that creates files with 3 parameters and no annotations or output schema, the description is incomplete. It doesn't cover error conditions, side effects, return values, or how the auto-detection works. Given the complexity and lack of structured data, more behavioral context is needed.
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%, so the schema already documents all three parameters with their types and defaults. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'autoDetect' interacts with 'projectPath' or what 'includeDefaults' actually includes. Baseline 3 is appropriate when schema does the heavy lifting.
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 the specific action ('Create a complete config.toml file from scratch') and resource ('config.toml file'), distinguishing it from siblings like 'validate_config' or 'generate_ci_config' by focusing on initial file creation with auto-detection capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for initial setup ('from scratch') and auto-detection based on project technologies, but doesn't explicitly state when to use this tool versus alternatives like 'validate_config' for existing files or 'generate_task' for individual tasks. No exclusions or prerequisites are mentioned.
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. It discloses the tool's behavior (parsing and listing tasks with specific fields) but lacks details on error handling, file format expectations, or performance characteristics. It adds basic context but misses deeper 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with zero waste, front-loading the core purpose and following with output details. Every word contributes to understanding the tool's function efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple input schema, the description is adequate for a basic read operation but lacks completeness. It explains what the tool does but not the return format, error cases, or dependencies, leaving gaps for an agent to infer behavior.
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%, so the schema fully documents the single parameter. The description does not add any parameter-specific information beyond what the schema provides, such as file format details or validation rules, meeting the baseline for high schema coverage.
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 the specific action ('Parse and list all tasks'), resource ('from a devpipe config.toml file'), and output details ('Shows task IDs, names, types, commands, and enabled status'). It distinguishes from siblings like 'list_tasks_verbose' by specifying the exact fields shown.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (working with devpipe config files) but does not explicitly state when to use this tool versus alternatives like 'list_tasks_verbose' or 'analyze_project'. It provides clear intent but lacks explicit comparison or exclusion 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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