Skip to main content
Glama
CatalystEdge

CatalystEdge

options_readiness

Verifies whether event and options evidence is complete enough for human review, helping confirm readiness before a catalyst decision.

Instructions

Check whether event and options evidence are complete enough for human review.

Input Schema

NameRequiredDescriptionDefault
as_ofNo
event_idYes
maximum_lossNo
implied_move_pctNo
bid_ask_width_pctNo
days_to_expirationNo
implied_volatility_pctNo
realized_volatility_pctNo
historical_event_move_pctNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden, and it reveals almost nothing: it never says whether the tool only reads evidence or also records a readiness state, what 'complete enough' means (criteria, thresholds), or what happens when evidence is missing. The output schema covers return values, but the behavioral profile of the call itself is undocumented.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero filler. It is efficient, though the brevity leaves the substance to the other dimensions rather than wasting words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter evaluation tool with no annotations, the definition is too thin: it never explains the readiness criteria, which evidence categories are required, or how the optional numerics influence the verdict. The presence of an output schema offsets only the return-value burden, not the invocation guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 9 parameters and 0% schema description coverage, the description must supply parameter meaning and supplies none. An agent cannot tell whether implied_move_pct, bid_ask_width_pct, maximum_loss, etc. are thresholds to compare against, overrides, or merely echoed values - a critical ambiguity for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Check') and object ('event and options evidence') with a clear goal: readiness for human review. It does not distinguish itself from the sibling 'event_readiness', leaving an agent to guess whether the difference is the inclusion of options data or something else.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Complete enough for human review' implies this is a gate to run before a review step, which is useful implied usage. But there is no explicit statement of when to prefer this over event_readiness or assess_event, and no preconditions or exclusions are given.

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