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

Annotations already cover readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is clear. The description adds that the tool emits Markdown and row chunks, but does not disclose what redaction looks like (placeholder vs. removal), whether redaction is reversible, or how prompt-injection findings are surfaced — the most consequential behaviors for a sanitizer.

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?

A single front-loaded sentence packs the value proposition and the three capabilities, followed by the endpoint. Nearly every phrase earns its place, though the endpoint note is low-value for an MCP caller and the marketing-style title is somewhat redundant.

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 5-parameter, no-output-schema transform tool, the description covers input domain, the three behaviors, and the shape of the returned data (Markdown plus row chunks). Combined with full schema coverage and rich annotations, an agent has enough to invoke it 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?

Schema description coverage is 100% and each flag is documented, so baseline is 3. The description only adds that input may be CSV or JSON and that RAG conversion happens; it does not explain how redact_pii, sanitize_formulas, and check_prompt_injection interact (e.g., disabling one) or what delimiter 'auto' actually detects.

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 names three concrete operations (neutralize CSV formula injection, redact cell-level PII, convert tables to RAG-ready Markdown and row chunks) on a specific resource (tabular CSV/JSON). That combination of tabular-only scope plus the three transforms distinguishes it from generic siblings like tinplate_pii_redactor and tinplate_rag_chunker without naming them.

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?

Usage is only implied by the described functions: an agent can infer 'use this before feeding tables into a RAG pipeline.' There is no explicit when-to-use, when-not-to-use, or named alternative such as the standalone PII redactor or chunker, so the agent must reason about routing itself.

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