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UnboundCompute

lachesis-mcp

Official

field_history

List initialization, modification, reads, checks, and value-flow events for any field, along with the owning functions, to trace dataflow and usage history.

Instructions

For a field/property, list graph-evidenced initialization, modification, reads, checks, and value-flow events with owning functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldYes
limitNo
formatNotext (compact, default) | json (structured result page)
offsetNo
owner_typeNooptional type name/id disambiguator
Behavior3/5

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

With no annotations, the description carries the full transparency burden. It conveys a read/list posture and adds meaningful context: results are graph-evidenced, oriented to field/property lifecycle events, and include owning functions. It does not disclose pagination behavior, ambiguity handling, or whether these events are purely inferred from an existing graph.

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?

One dense, front-loaded sentence. It opens with the resource ('For a field/property') and packs the important event taxonomy into a compact list without repetition or filler.

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

Completeness3/5

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

For a 5-parameter tool with no output schema, the description is only minimally complete. It specifies the result content (event types and owning functions), but leaves important context implicit: how the 'field' is represented, how owner_type disambiguates, and how limit/offset shape the returned page.

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

Parameters3/5

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

The schema covers only 40% of parameters with descriptions. The tool description partially compensates by clarifying that the field parameter refers to a field/property and that owning functions are part of the output. It does not explain field-name syntax or the relationship between field and owner_type beyond what the schema already provides.

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 a verb ('list') and a resource ('field/property') and enumerates specific event categories: initialization, modification, reads, checks, and value-flow events. It does not explicitly name sibling tools that overlap (e.g., flow, sources_of), so it stops short of full sibling differentiation.

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?

The phrase 'For a field/property' gives a clear implied usage context, and listing event history is a reasonable trigger condition. However, it gives no explicit 'when not to use' guidance and does not compare against alternatives like flow or object_lifecycle.

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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