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

With no annotations provided, the description carries the transparency burden and discloses substantial behavioral detail: exact GO conditions, the KILL gate, and the observer-invariance of fatal verdicts. It does not discuss side effects or error behavior, but for a compute-style tool the disclosed thresholds and branching behavior are the most important traits.

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-loads the most decision-relevant information: the GO/KILL thresholds and the observer pipeline. The middle sentence is a dense run-on list, but every clause contributes meaning and there is no filler.

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?

The core algorithm and observer branch are well covered, but this is a complex 7-parameter tool with nested objects, low schema description coverage, and no output schema. The description does not explain the returned verdict structure or the roles of several optional parameters, so an agent cannot fully anticipate behavior for all valid inputs.

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 description adds real meaning to lensScores and stage by explaining how scores, red flags, confidence, and stage-aware weights drive the verdict, and it clarifies how the observer object perturbs weights and thresholds. However, schema description coverage is only 14%, and the description says nothing about sector, stageProbabilities, hasMajorContradiction, or unresolvedContradictions, leaving their roles to inference.

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 identifies the tool as a methodology-v2 dealbreaker computation and states its core mechanics: stage-aware weights, confidence-weighted lens scoring, and risk-asymmetric verdict logic. It also distinguishes the tool from generic compute siblings by specifying GO/KILL thresholds and the observer-triggered crossed-product pipeline.

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 gives parameter-level usage guidance: omit observer for the substrate baseline, include it for the crossed verdict and archetype matrix. However, it never explicitly says when to prefer this tool over sibling alternatives like compute_crossed_matrix or derive_kill_criteria, so the usage guidance remains mostly implied.

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