MCP Project Context Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting different project management functions: project creation/listing, session management, task/note/decision handling, and context retrieval. No tools overlap in functionality, making selection straightforward for an agent.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern (e.g., add_note, create_project, get_project_context) with clear, descriptive action-object pairs. There are no deviations in style or convention across the set.
Tool Count5/5
With 9 tools, the server is well-scoped for project context management, covering core operations like project lifecycle, session handling, and task/note/decision tracking. Each tool earns its place without bloat or gaps.
Completeness4/5
The toolset provides strong coverage for project context workflows, including CRUD-like operations for projects, tasks, notes, and decisions, plus session management. A minor gap exists in updating or deleting notes/decisions, but agents can work around this with the available tools.
Average 2.9/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 full burden. 'End current session with summary' implies a mutation (ending something) but doesn't disclose behavioral traits like whether this is destructive, what happens to session data, if it requires specific permissions, or what the summary output looks like. It lacks details on side effects or system behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action ('End current session') and adds a clarifying detail ('with summary'). Every word earns its place, making it highly concise and well-structured.
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 no annotations, no output schema, and a mutation tool (implied by 'End'), the description is incomplete. It doesn't explain what 'ending a session' means in this context, what the summary includes, or what the tool returns. For a tool with 4 parameters and potential side effects, more context is needed to guide the agent 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?
Schema description coverage is 100%, so the schema fully documents all 4 parameters. The description adds no parameter semantics beyond what's in the schema—it doesn't explain how 'achievements', 'blockers', or 'nextSession' relate to the summary or session ending. Baseline 3 is appropriate as the schema handles parameter documentation.
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 'End current session with summary' states the verb ('End') and resource ('current session'), but it's vague about what 'with summary' entails. It doesn't clearly distinguish this tool from sibling tools like 'start_session' or explain what ending a session actually does beyond the summary aspect.
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., must have an active session), exclusions, or relationships to sibling tools like 'start_session' or 'add_note'. The agent must infer usage from 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?
With no annotations, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention if this creates persistent resources, requires authentication, has side effects, or what happens upon success/failure, which is inadequate for a tool that likely initiates a stateful process.
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 with zero wasted words. It's front-loaded and appropriately sized for the tool's apparent complexity, making it easy 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 no annotations, no output schema, and a tool that likely creates a stateful session, the description is incomplete. It doesn't explain what a session is, what it enables, or what the agent should expect after invocation, leaving significant gaps for effective tool 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%, so the schema already documents both parameters (projectId and goals). The description adds no meaning beyond this, such as explaining how goals influence the session or what projectId references. Baseline 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Start a new development session' clearly states the action (start) and resource (session), but it's vague about what a 'development session' entails and doesn't distinguish from sibling tools like 'end_session' or 'create_project'. It's functional but lacks specificity.
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 like 'create_project' or 'end_session'. The description implies initiation but doesn't specify prerequisites, timing, or exclusions, leaving the agent to infer usage 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 full burden. It states 'Add a note' which implies a write operation, but doesn't disclose behavioral traits such as permissions required, whether notes are editable/deletable, rate limits, or what happens on success/failure. This is a significant gap for a mutation tool.
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 with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without 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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error handling, or return values, leaving significant gaps for an AI agent to understand how to use it correctly.
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 (projectId, content, category) with basic descriptions. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add') and target ('note to the project'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'record_decision' or 'add_task', which might also involve adding content to projects, so it lacks sibling distinction.
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. With siblings like 'add_task', 'record_decision', and 'create_project', there's no indication of when a note is appropriate versus other types of project additions or updates.
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 this is an 'Add' operation, implying a write/mutation, but doesn't address permissions, side effects, error conditions, or what happens on success (e.g., returns a task ID). For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly without 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 mutation tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, authentication requirements, or how it differs from sibling tools. The combination of write operation complexity and lack of structured metadata requires more descriptive context than provided.
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 clear documentation for all 5 parameters including types, required status, enums for priority, and defaults for tags. The description adds no parameter-specific information beyond what's in the schema, so it meets the baseline for high schema coverage without compensating with extra semantic context.
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 ('Add') and resource ('new task to the project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_task' or 'create_project', which would require more specific language about what makes this tool unique for task creation versus project creation or task modification.
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 like 'update_task' or 'create_project'. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage based solely on the tool name and basic purpose.
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 'Create' implies a write operation, the description doesn't address permissions required, whether the operation is idempotent, what happens on duplicate names, or what the response contains. For a mutation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 perfectly concise at 6 words, front-loading the essential action. Every word earns its place: 'Create' (verb), 'new project' (resource), 'with initial context' (scope). There's no wasted language 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 creation tool with 4 parameters (including a complex nested object), no annotations, and no output schema, the description is insufficient. It doesn't explain what 'initial context' means, what happens after creation, or provide any behavioral context. The agent would need to guess about the tool's full behavior and output.
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?
With 75% schema description coverage, the schema already documents most parameters well. The description adds minimal value beyond what's in the schema - 'initial context' vaguely relates to parameters but doesn't explain how 'techStack' or 'currentPhase' contribute to that context. The baseline of 3 is appropriate given the schema does substantial documentation work.
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 ('Create') and resource ('new project'), making the purpose immediately understandable. It distinguishes from siblings like 'list_projects' or 'get_project_context' by specifying creation rather than retrieval. However, it doesn't explicitly differentiate from potential similar creation tools that might exist in other contexts.
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. There's no mention of prerequisites, when this should be used instead of other project-related tools, or what constitutes 'initial context' that would trigger its use. The agent must infer usage from 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 'gets' information, implying a read-only operation, but doesn't clarify permissions, rate limits, or what 'comprehensive context' entails (e.g., includes tasks, notes, decisions). For a tool with no annotations, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Get comprehensive project context and current state'. It's front-loaded with the core purpose and avoids unnecessary words. However, it could be slightly more specific without losing 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 (retrieving project context), no annotations, no output schema, and a simple input schema, the description is minimally adequate. It states what the tool does but lacks details on return values, behavioral constraints, or usage context. It meets the bare minimum for a read operation but leaves the agent guessing about the output format and scope.
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 input schema has 100% description coverage, with the single parameter 'projectId' documented as 'Project ID'. The description doesn't add any parameter-specific details beyond what the schema provides, but with only one parameter and high schema coverage, the baseline is high. No additional value is added, but no compensation is needed.
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's purpose as 'Get comprehensive project context and current state', which is clear but vague. It specifies the verb 'Get' and resource 'project context', but doesn't distinguish it from potential sibling tools like 'list_projects' or provide specifics about what 'comprehensive context' includes. This is adequate but lacks differentiation.
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. With siblings like 'list_projects' and 'create_project', there's no indication of when this retrieval tool is appropriate versus listing or creating projects. The agent must infer usage from the 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. 'Record' implies a write operation, but the description doesn't specify whether this creates a new record, updates an existing one, requires permissions, has side effects, or what the response looks like. It lacks details on persistence, error handling, or any behavioral traits beyond the basic action.
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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes directly to understanding the tool's purpose, achieving optimal conciseness.
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 a write operation with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like what happens after recording, error conditions, or return values. For a tool that likely mutates data, more context is needed to guide the agent effectively, leaving significant gaps in 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%, with clear descriptions for all parameters (e.g., 'Decision made', 'Reasoning behind the decision'). The description adds no additional semantic context beyond what the schema provides, such as examples or usage notes. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but there's no extra value from the description.
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 'record' and the resource 'architectural or technical decision', making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'add_note' or 'add_task', which might also record information but for different types of content. The description is specific about what kind of decision is being recorded.
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., during project planning), or exclusions. With siblings like 'add_note' and 'add_task', there's no indication of how this tool differs in usage, leaving the agent to guess based on tool names 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 states this is an update operation (implying mutation) but doesn't mention required permissions, whether changes are reversible, error handling, or what happens to existing fields not specified. This leaves significant behavioral gaps for a mutation tool.
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 communicates the core purpose without any wasted words. It's appropriately sized and front-loaded with essential information.
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 with 6 parameters and no annotations or output schema, the description is inadequate. It doesn't explain what happens when only some fields are provided, whether updates are partial or complete, what the response looks like, or any error conditions. The description should provide more context given the complexity and lack of structured metadata.
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 schema description coverage is 100%, so all parameters are documented in the schema. The description mentions 'status or details' which aligns with the schema's parameters (status, title, description, priority), but adds no additional semantic context beyond what the schema already provides. 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 verb ('Update') and resource ('task') along with what can be updated ('status or details'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'add_task', but the 'update' vs 'add' distinction is implied through the naming convention.
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 like 'add_task' or 'record_decision', nor does it mention prerequisites or context for updating tasks. It simply states what the tool does without any usage 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. It states the ordering behavior ('ordered by last accessed'), which is useful. However, it lacks critical details: whether it's paginated, what fields are returned, if it requires authentication, or any rate limits. For a list operation with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It front-loads the core action ('List all projects') and adds a useful constraint ('ordered by last accessed') without 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 no annotations and no output schema, the description is incomplete. It doesn't explain the return format, pagination, or authentication needs. For a list tool that likely returns multiple items, this leaves the agent with insufficient context 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds no parameter information, which is appropriate. Baseline is 4 for zero parameters, as the schema fully covers the absence of inputs.
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 ('List') and resource ('projects') with a specific ordering constraint ('ordered by last accessed'). It distinguishes from siblings like 'create_project' by indicating retrieval rather than creation. However, it doesn't explicitly differentiate from potential other listing tools (though none are present in the sibling list).
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, or compare with siblings like 'get_project_context' for specific project details. The agent must infer usage solely from the tool name and description.
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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