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UnboundCompute

lachesis-mcp

Official

flow

Trace a value's forward dataflow through pointers and aliases to see all downstream destinations.

Instructions

Read-only. Forward value-flow cone from a value/symbol: everything it can reach over VALUE_FLOWS_TO + POINTS_TO, bridging aliases through the heap. Use it to answer 'where does this value go?'; for the reverse (what feeds a sink) use sources_of, and for a yes/no witness between two points use reaches. Returns labeled nodes/edges; a missing path is over-approximation-safe, not proof of none.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedYesvalue/symbol name or graph node id to flow from
limitNomaximum nodes returned
formatNotext (compact, default) | json (structured result page)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv0.2.0
    • addedInput schema / properties / limit / description
      Added value: +"maximum nodes returned"
    • addedInput schema / properties / seed / description
      Added value: +"value/symbol name or graph node id to flow from"
  2. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers: declares read-only safety, discloses the return shape (labeled nodes/edges), and — most valuably — states the over-approximation caveat that a missing path is not proof of absence. Also reveals the algorithmic behavior of bridging aliases through the heap.

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?

Three sentences with zero waste: what+relations, when+alternatives, return+caveat each earn their sentence. The read-only flag and core action are front-loaded for immediate orientation.

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?

Strongly complete for a complex graph-analysis tool with no output schema: selection guidance, safety profile, return format, and the key soundness caveat are all present. Minor gap: the interaction between limit=200 truncation and the 'missing path is over-approximation-safe' claim is not addressed.

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?

Schema covers 100% of parameters, so seed, limit, and format are already documented there. The description adds some semantic color (traversal over VALUE_FLOWS_TO + POINTS_TO, 'from a value/symbol'), but this mostly reinforces the schema's seed description rather than expanding on it. Baseline 3 is appropriate.

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

Purpose5/5

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

States a precise verb+resource pair ('Forward value-flow cone') and the exact graph relations involved (VALUE_FLOWS_TO + POINTS_TO), including alias-bridging through the heap. This sharply distinguishes it from the sibling set — sources_of (reverse direction) and reaches (yes/no witness) are explicitly named as different tools.

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

Usage Guidelines5/5

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

Gives an explicit selection rule — 'Use it to answer where does this value go?' — and names the two closest alternatives with their exact conditions: sources_of for the reverse (what feeds a sink) and reaches for a yes/no witness. An agent can route correctly with zero inference.

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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