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alshyra

Sherlock's second brain

case_update

Append new findings, steps, conclusions, hypotheses, tags, and references to an existing investigation case.

Instructions

Append to a case.

fields supports:

  • finding (str): append to findings

  • step_action (str): append a step (with optional step_result)

  • step_result (str): result for the step being appended

  • conclusion (str): set conclusion

  • hypothesis_statement / hypothesis_test: append a hypothesis

  • tags (list[str]) / references (list[str]): replace lists

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYes
case_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full burden and does disclose important field-level behavior (append vs. set vs. replace lists). It omits permission requirements, error behavior, and response details, leaving clear gaps for a mutating tool.

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

Conciseness5/5

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

The description is front-loaded with a one-line action and followed by a tight, well-organized bullet list of field behaviors. Every line provides distinct information and there is no filler or repetition.

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

Completeness4/5

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

The description covers all supported field modes and field relationships (step_action/step_result pair) and correctly leaves return details to the existing output schema. It lacks explicit prerequisites and error conditions, but is otherwise complete for a field-update tool.

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

Parameters5/5

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

The input schema is opaque for fields (additionalProperties true, 0% description coverage), so the description’s enumerated list of supported fields with their value types and semantics is essential. It gives the agent concrete, actionable meaning beyond the raw schema.

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?

The description clearly states the action as 'Append to a case' and lists the supported field categories, which gives a specific verb and resource. However, it does not explicitly differentiate itself from sibling tools like case_add_evidence or case_set_status.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as case_add_evidence or case_set_status. It only describes what fields can be updated, leaving the choice of tool implicit.

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

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