Skip to main content
Glama

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: summarizing state, listing projects, recording entries, searching, and updating. No overlapping functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (e.g., get_project_state, record_project_entry), ensuring predictability.

    Tool Count5/5

    With 5 tools, the server covers essential operations without being overwhelming or insufficient for project state management.

    Completeness4/5

    Covers core operations (list, get, record, search, update) but lacks explicit project creation and deletion, which may be minor gaps.

  • Average 3.4/5 across 5 of 5 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 9 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 provided, so description must disclose behavioral traits. It only says 'Stores' without clarifying if entries are appended or overwritten, or if duplicates are allowed.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence is concise but omits important details. While not verbose, it does not fully earn its place given the missing behavioral and usage 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?

    No output schema and description does not mention return value or success/error behavior. Does not explain whether entries are idempotent or require prior project existence.

    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 has 100% coverage with descriptions for all parameters. Description adds no extra meaning beyond the schema, such as value formats or constraints.

    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?

    Description clearly states it stores a structured project-state entry and lists the allowed categories. It distinguishes from siblings like get_project_state (read) and update_project_entry (update).

    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 update_project_entry or whether the project must already exist. Lacks prerequisites or exclusions.

    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. It states the output is 'concise, readable summary, grouped by category' but does not disclose read-only nature, performance, or any side effects. Minimal behavioral insight.

    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?

    Single sentence, no fluff, front-loaded with verb and object. Every word adds value.

    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?

    For a simple read tool with full schema parameter coverage and no output schema, the description adequately conveys categorization. However, it does not specify what 'state' includes (e.g., status, metrics), leaving some ambiguity.

    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 coverage is 100% with clear parameter descriptions. The description adds 'grouped by category' hinting at the category parameter, but this is already implied by the parameter description. Meets baseline.

    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 uses a specific verb 'Returns' and resource 'summary of project state' making the purpose clear. It implicitly distinguishes from siblings like list_projects (list only) and search_project_state (search), but does not explicitly differentiate.

    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 such as search_project_state or list_projects. The description provides no context for selection.

    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 must fully disclose behavioral traits. It only mentions 'simple keyword query' without explaining output format, pagination, case sensitivity, wildcards, or any side effects. This minimal information is insufficient for an agent to understand the tool's behavior beyond the basic intent.

    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, concise sentence with no extraneous words. However, it lacks structure such as front-loading key details or breaking down complex information. While efficient, it could be slightly more informative without losing 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 absence of an output schema and annotations, the description should explain what the search returns. It does not mention the return format, whether results are filtered or sorted, or any limitations. This leaves a significant gap in context for the agent to correctly invoke and interpret the tool's 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?

    The input schema provides full descriptions for both parameters ('project' and 'query'), achieving 100% coverage. The description adds only the qualifier 'simple', which does not significantly enhance meaning beyond the schema. Therefore, it meets the baseline for high schema coverage without adding substantial value.

    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 action ('Search'), the resource ('project state ledger'), and the method ('simple keyword query'). It effectively distinguishes this tool from its siblings (get_project_state, list_projects, record_project_entry, update_project_entry) by indicating a different purpose: searching instead of retrieving full state, listing, recording, or updating.

    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 keyword-based searching but does not explicitly state when to use this tool versus alternatives. No guidance on when not to use it or which sibling might be better suited for specific scenarios is provided, leaving the agent to infer 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 exist, so the description must fully disclose behavior. It only states it returns a list; no mention of pagination, ordering, performance characteristics, or potential large results. This lack of detail can cause agent uncertainty.

    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?

    Extremely concise single sentence with no wasted words. All information is front-loaded and clear.

    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 parameters or output schema, the description is minimal. It covers the basic purpose but lacks details on return format, ordering, or any limitations. For a simple listing tool, it is adequate but could be more complete (e.g., 'Returns an array of project objects with id and name').

    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?

    No parameters exist, and schema coverage is 100%. Baseline score of 4 applies as description adds no parameter info but is not needed. The tool has no parameters to document.

    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 it returns a list of all known projects tracked by Samskriti V1, with a specific verb and resource. It distinguishes from siblings like get_project_state (single project) and search_project_state (filtered).

    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 like search_project_state for filtered results. The description implies listing all projects but does not explicitly state when to prefer this tool.

    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, and the description does not disclose behavioral traits such as permissions, idempotency, side effects, or error handling. For a mutation tool, 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 sentence of 10 words, front-loaded with the action and resource, with no extraneous information. Every word earns its place.

    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?

    For a simple update tool with no output schema, the description covers the what and the modifiable fields. However, it lacks information on return values, error conditions, or idempotency, which would be helpful for an AI agent.

    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 description adds value by listing the allowed status values in parentheses, which is not fully captured in the schema's description for the 'status' parameter. Schema coverage is 100%, so baseline is 3; the extra enum detail raises it to 4.

    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 uses the specific verb 'Update' with the resource 'project entry' and lists the fields that can be modified (title, content, status). It clearly distinguishes from sibling tools like 'record_project_entry' (create) and 'get_project_state' (read).

    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 implicitly conveys usage: modify an existing entry. However, it does not explicitly state when not to use it (e.g., for creating new entries) or provide alternatives. Despite this, the context is clear given the sibling tool names.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

samskriti-shared-layer MCP server

Copy to your README.md:

Score Badge

samskriti-shared-layer MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Escalate17/samskriti-shared-layer'

If you have feedback or need assistance with the MCP directory API, please join our Discord server