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Glama

Get validation project

validation.get_project
Read-onlyIdempotent

Retrieve one private validation project and its saved analysis results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
validation_project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context by specifying 'private' and that saved analysis results are included, but it does not disclose behaviors like authorization requirements or what happens when the project is not found. No contradiction with annotations exists.

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, front-loaded sentence with no filler or redundant restatement of the tool name. Every word adds value by conveying scope, privacy, and result content.

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-only getter with annotations and an output schema, the description is reasonably complete. However, the missing explanation of the two IDs and how they relate leaves a notable gap for correct invocation, especially given the schema has no descriptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden of explaining parameters, but it does not mention validation_project_id or project_id at all. The parameter names are somewhat self-explanatory, yet the description adds no meaning about their relationship or required values.

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 a specific verb ('Retrieve') and names a precise resource ('one private validation project') with its associated results. It clearly distinguishes itself from sibling tools like validation.list_projects by emphasizing 'one' and from validation.start_analysis by mentioning saved analysis results.

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 makes it clear that the tool retrieves an existing project/results, so an agent can infer when to use it over list/create/start tools. However, it does not explicitly mention list_projects as the alternative for retrieving multiple projects or state any when-not-to-use conditions.

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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TDQS

B3.1/5.0
Disambiguation3/5

Domain prefixes (crm., cap_table., landing.) clearly separate broad modules, and most tools target a specific resource and action. However, within modules there are boundary overlaps—crm.add_contact_note vs crm.log_activity and cap_table.dilution_preview vs cap_table.simulate_raise—where descriptions must be read carefully to avoid a wrong pick.

Naming Consistency3/5

The dominant pattern is module.verb_noun (e.g., crm.create_lead, cap_table.update_stakeholder), which is clear and readable. But a subset of top-level tools uses object_verb with flat underscores (e.g., shortlink_create, qr_generate, campaign_archive) and one outlier (campaign_stats) breaks the verb pattern, so conventions are mixed.

Tool Count1/5

86 tools is an extreme surface for any single MCP server, well past the 50+ threshold that makes coherent selection impractical. Even though the features span several business domains, this would be far more usable split into focused servers per module.

Completeness4/5

The covered domains are broadly complete: cap table, CRM, incorporation, landing, projects, sparkroom, tasks, and validation all have read/write workflows with few dead ends. Minor gaps remain (no campaign listing/update, no branding palette delete/update, no contact deletion) but none of them blocks the main product workflows.

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