update_company_tech_stackUpdate your company's tech stack on Himalayas. Pass technology names (e.g., 'React', 'Python') and they'll be matched to the Himalayas stack database. Uses the connected Himalayas employer account; no extra sign-in needed.
| Name | Required | Description | Default |
|---|---|---|---|
| stacks | Yes | Array of technology names (e.g., ['React', 'TypeScript', 'Python', 'AWS']) |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Input schema / additionalPropertiesRemoved value: -falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, idempotentHint=true, and readOnlyHint=false, so the write/replace risk is flagged structurally. The description adds the non-obvious behavior that input names are fuzzy-matched against the Himalayas stack database, but it omits the critical question of whether the passed array replaces the entire stack or merges with existing entries — a significant gap given destructiveHint=true.
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?
Three short sentences with the core action front-loaded and no filler. Slightly padded by the 'no extra sign-in needed' clause, but every sentence is relevant.
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?
For a single-parameter mutation with no output schema, the description covers input handling and auth, and annotations cover safety hints. It is still incomplete on the replace-vs-append semantics and on what confirmation or matched-result the agent gets back, which matters for a destructive write.
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?
Schema description coverage is 100% on the single 'stacks' parameter, including its own example array, so the schema already carries parameter meaning. The description's mention of matching technology names to the database adds a little semantic context but no syntax or format detail beyond the schema. Baseline 3 applies.
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 gives a specific verb+resource ('Update your company's tech stack on Himalayas') and scopes it to the company entity, which separates it from the sibling update_tech_stack. It stops short of explicitly naming that sibling, so differentiation is inferable rather than stated.
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?
It provides useful context that no separate sign-in is required because it uses the connected employer account, but it never states when to use this tool versus the personal update_tech_stack or how it relates to update_company_profile. Usage is implied rather than guided.
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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