approve_consulting_deliverableApprove one submitted internal deliverable and record approver evidence. Requires consulting:approve and never publishes or sends it.
| Name | Required | Description | Default |
|---|---|---|---|
| deliverable_id | Yes | ||
| expected_version | Yes | ||
| expected_content_hash | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which are all false), the description adds that the tool 'requires consulting:approve' and 'never publishes or sends it', clarifying that it is a mutation but with limited external side effects. However, it could further detail what happens upon approval (e.g., status changes).
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 two sentences, front-loaded with the core purpose, and includes essential constraints without extraneous text. Every sentence adds value.
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?
Given the three required parameters with no schema descriptions, the description fails to provide necessary guidance on how to use them effectively. Although an output schema exists, the lack of parameter semantics leaves the tool incomplete for an agent to invoke correctly.
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 input schema has 0% description coverage, and the tool description does not explain any of the three required parameters (deliverable_id, expected_version, expected_content_hash). The agent is left guessing about their purpose and format beyond what the schema provides, which is insufficient.
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 the verb 'Approve' and the resource 'one submitted internal deliverable', and it distinguishes from sibling tools like 'approve_consulting_document_revision' and 'submit_consulting_deliverable' as it explicitly says 'submitted internal deliverable' and 'never publishes or sends it'.
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?
The description implies usage for internal approval but does not explicitly state when to use it versus alternatives. It mentions the required permission 'consulting:approve' but does not name alternative tools or conditions for when not to use this tool.
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.
Every tool targets a distinct resource and action, with detailed descriptions that clearly separate overlapping domains (e.g., consulting vs. marketing vs. outreach). Even within the same domain, tools like 'create_consulting_deliverable' and 'create_consulting_document_revision' are unambiguous due to their specific nouns.
All tools follow a consistent verb_noun snake_case pattern (e.g., 'create_invoice', 'get_deal', 'list_agents'). The few exceptions like 'locus_determine_from_scores' still adhere to the verb_noun structure and do not break the pattern.
With 124 tools, the server is massively over-scoped for typical MCP use. The tool count far exceeds the '50+ extreme mismatch' threshold, making it nearly impossible for an agent to efficiently navigate or select the right tool without extensive context. Even a large platform should consolidate or expose fewer tools.
The tool surface covers CRUD and lifecycle operations across at least 10 domains (sales, consulting, marketing, outreach, accounting, workflows, ticketing, API keys, feedback, platform metrics). Each domain appears to have no obvious gaps—e.g., invoicing includes create, update, send, mark paid, void; ticketing includes create, update, archive, dependencies, batch, scenarios, validation.