analyze_projectAnalyze a project for audience, positioning, differentiators, content pillars, and risks.
| Name | Required | Description | Default |
|---|---|---|---|
| team_id | No | Optional team ID or slug. Ignored when using a team-scoped API key. | |
| projectId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations indicate readOnlyHint=false and openWorldHint=true, implying potential side effects or external effects, but the description does not clarify what these side effects might be. It also does not mention return format, required permissions, or any behavioral details beyond the basic analysis action, so the agent is left uninformed about the tool's non-read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and lists the analysis areas concisely. Every word is useful and there is no unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, and the description does not describe what the analysis returns or what side effects occur. Since annotations suggest a non-read-only and open-world nature, the description should explain what changes or outputs result from the analysis, but it only lists topics without clarifying the outcome or execution context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has only 50% description coverage, with projectId left undocumented. The description does not mention either parameter (projectId or team_id) and provides no guidance on how to specify the project for analysis, offering no added meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool analyzes a project and specifies the dimensions covered (audience, positioning, differentiators, content pillars, risks). However, it does not differentiate from the sibling tool 'get_project_analysis', which likely has a similar purpose, so it misses the opportunity to distinguish itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. The description only implies generic usage for project analysis, with no mention of prerequisites, exclusions, or related tools such as 'get_project_analysis' or 'generate_project_strategy'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With 148 tools, there is significant overlap. For example, generate_content, publish_ai, generate_post_bundle, and request_project_content all generate content; get_analytics, get_unified_analytics, get_post_analytics, get_ad_performance, and get_unified_ad_report all fetch performance metrics; and list_inbox vs list_conversations blur comment and conversation management. Descriptions help, but boundaries between tools are often unclear.
Most tools follow a verb_noun pattern (e.g., list_teams, create_goal, delete_post), but there are notable deviations: create_library_item vs save_to_library, publish_content vs publish_ai, schedule_content vs schedule_content_advanced, and connect_platform vs connect_connector. Mixed prefixes like 'autopilot_', 'check_', and 'get_' are fine, but overlapping verbs and a hyphen in 'connect_linkedin-page' reduce consistency.
148 tools is extreme for any server. Even for a broad social media management platform, this is far beyond what an agent can effectively navigate. The count is unwieldy and suggests the surface should be split into multiple focused servers (publishing, analytics, connectors, workflows, etc.).
The core social publishing workflow is well covered (create, schedule, publish, edit, delete, retry), and there are extensive features for analytics, workflows, connectors, and AI agents. However, some resources have CRUD gaps: no update/delete for brand voices, no delete_project, no update/delete for Product Hunt goals, and no explicit get_workflow. These are workable but notable omissions.