Compute Topological Fingerprint (TDA)

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

Discloses behavior beyond annotations: fetches AlphaFold model, runs persistent homology (with fallback if gudhi missing), returns no-structure result when model absent, explains Betti numbers and invariance. Annotations already indicate readOnly and idempotent, but description adds rich behavioral context.

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?

Description is well-structured with clear paragraphs and front-loaded purpose. While slightly long, every sentence provides valuable information about behavior, use cases, and limitations. Could be trimmed slightly but is justified.

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 existence of an output schema, description still explains return values (fingerprint vector, Betti numbers, residue count, method flag) and edge cases (no-structure result, fallback). Covers all necessary context for a complex tool.

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 has one parameter 'uniprot_id' with description and regex pattern. Description adds context by explaining it is used to fetch AlphaFold model, which provides meaning beyond the schema description. However, schema coverage is already good, so marginal added value.

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?

Description clearly states 'Compute a rotation-invariant topological fingerprint of a protein's fold.' It uses specific verb (compute), resource (topological fingerprint), and domain (protein). Mentions sibling tools that consume these fingerprints, distinguishing it from other structure-related tools.

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?

Explicitly says 'Use it as the per-protein input to structure-similarity comparisons: compare_proteins_topologically and find_evolutionary_structural_shifts consume these fingerprints.' Also states what it is not a substitute for (sequence alignment, RMSD, functional-homology), providing clear when-to-use and when-not-to-use guidance.

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