headlo-mcp

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create_expert_protocol

Creates a Context Accumulation Protocol (CAP) for a Headlo Ask question, building structured intake questions and research-backed knowledge probes to capture expert answers.

Instructions

Create a CAP (Context Accumulation Protocol) for a question on the Headlo Ask network. Before writing any knowledge probes, always do a web search to gather current, specific facts. Each probe answer must contain 4–6 specific facts sourced from your research.

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": {
      "bounty_id": "<bounty_id>",
      "questions": "<questions>"
    },
    "name": "create_expert_protocol"
  }
}

Input Schema

Name	Required	Description	Default
`bounty_id`	Yes	ID of the question to create the protocol for. Found in the question URL: headlo.com/plugin/ask/{bounty_id}
`questions`	Yes	Intake questions with expert knowledge probes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2Aug 6, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations provided, the description bears the full responsibility for behavioral disclosure. It does reveal important constraints (web search requirement, 4–6 facts per answer), but it omits side effects (e.g., whether existing protocols are overwritten), permission requirements, or return behavior. This is a moderate disclosure level for a create operation.

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 two sentences long, with the purpose clearly front-loaded in the first sentence. It wastes no words and conveys the essential process requirement in the second sentence, earning a high score for conciseness and structure.

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?

The tool has a complex nested schema, but the description is brief (only two sentences). While the schema covers parameter meanings, the description omits contextual information such as when to use the tool, what happens upon creation, or how the protocol will be used afterward. It is adequate but leaves noticeable gaps for a create tool with this level of complexity.

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

Parameters4/5

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

The input schema already has 100% coverage with descriptive parameter text, so the baseline is 3. The description adds meaningful value beyond the schema by specifying that each probe answer must contain 4–6 specific facts sourced from research, which directly informs the 'answer' field and enforces an expected quality level.

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 ('Create a CAP') and the specific resource ('Context Accumulation Protocol for a question on the Headlo Ask network'), which distinguishes it from generic create tools. However, it does not explicitly contrast with similarly named siblings like cap_capture_expert or cap_edit_expert, leaving some ambiguity in tool selection.

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 procedural guidance ('always do a web search before writing any knowledge probes') but does not explain when to use this tool versus alternatives like cap_capture_expert or cap_edit_expert. There is no explicit mention of use cases, exclusions, or prerequisites, so the agent receives little help in deciding to invoke this tool.

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