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SimpleFunctions

SimpleFunctions

by spfunctions
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

trigger_evaluation

Trigger immediate thesis evaluation: consume pending signals, re-scan edges, and update confidence scores. Ideal after inject_signal to get fresh results now without waiting for scheduled re-evaluation.

Instructions

Force an immediate thesis evaluation: consumes pending signals, re-scans edges, and updates confidence scores. Side-effectful and LLM-billed (typically 5-30s, may be rate-limited per plan). Requires SF API key. Use after inject_signal when you need fresh output now; otherwise theses re-evaluate on their own schedule.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "thesisId": "<thesisId>",
      "apiKey": "<apiKey>"
    },
    "name": "trigger_evaluation"
  }
}

Input Schema

NameRequiredDescriptionDefault
thesisIdYesTarget thesis ID. Required. Get one from list_theses.
apiKeyYesSF API key (sf_live_...). Required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.2
    • addedInput schema / properties / apiKey / description
      Added value: +"SF API key (sf_live_...). Required."
    • addedInput schema / properties / thesisId / description
      Added value: +"Target thesis ID. Required. Get one from list_theses."
  2. First observedv0.1.1

TDQS

A4.6/5.0
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses side-effectfulness, LLM billing, typical latency (5-30s), rate limits, and requirement for SF API key. No contradiction.

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 concise sentences front-loaded with purpose and effect, followed by usage context and when-to-use. No wasted words.

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?

Given no output schema, description explains what happens (updates confidence scores) but lacks detail on return value. Still sufficient for a trigger action.

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 coverage is 100%, so baseline is 3. Description does not add meaning beyond schema's parameter descriptions: thesisId and apiKey are required, apiKey format hinted elsewhere.

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?

The description clearly states the tool forces an immediate thesis evaluation, consuming pending signals, re-scanning edges, and updating confidence scores. This distinguishes it from sibling tools like inject_signal (which injects signals) and list_theses (which lists theses).

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?

Explicit guidance: use after inject_signal when fresh output is needed immediately; otherwise, theses re-evaluate automatically. This provides clear when-to-use and when-not-to-use context.

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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