cachly-mcp-server

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: lessons are stored with a specific prefix ('cachly:global:lesson:'), are accessible from any instance via 'global_recall', and apply globally. However, it doesn't mention persistence, storage limits, or error handling, leaving some gaps for a mutation tool.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by storage details, usage context, and a concrete example. Every sentence earns its place by adding value without redundancy.

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 tool's complexity (a mutation with 5 parameters, no annotations, and no output schema), the description is mostly complete. It covers purpose, usage, and storage behavior but lacks details on return values or error cases. The absence of an output schema means the description should ideally hint at what's returned, but it compensates well with clear behavioral 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description doesn't add meaning beyond what the schema provides (e.g., it doesn't explain 'topic' format beyond the schema's 'category:keyword' or give more context for 'severity' levels). Baseline 3 is appropriate as the schema does the heavy lifting.

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 tool's purpose: 'Store a lesson that applies across ALL your projects (cross-project knowledge).' It specifies the verb ('store'), resource ('lesson'), and scope ('across ALL projects'), distinguishing it from sibling tools like 'team_learn' or 'learn_from_attempts' which likely have different scopes. The example further clarifies the action.

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 explicitly states when to use this tool: for 'cross-project knowledge' and provides specific use cases ('tool preferences, personal workflows, platform quirks, and universal gotchas'). It also mentions the complementary tool 'global_recall' for retrieval, clearly differentiating it from project-specific or team-based learning tools in the sibling list.

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