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Add people to a Bullseye Test

bullseye_add

Add people to a Bullseye Test™'s list, up to 200 a call: each one who said in public that they have the problem, with the channel that reaches them. email: an address they published or one that checked out (never guessed, never catch-all). x_dm: only when their X inbox is open (checked in the founder's Chrome; a closed inbox is not counted as reached). reddit_dm: their Reddit username. opener: one line written from their own post, the first line of their message. Each person is kept once across every test, and nobody outbound already wrote to (by handle or address) is added. Free.

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": {
      "people": "<people>"
    },
    "name": "bullseye_add"
  }
}

Input Schema

NameRequiredDescriptionDefault
idNoThe test; default the newest open one
peopleYesEach { platform: x|reddit|hn|other, handle, name?, email?, channel: email|x_dm|reddit_dm, post?: { url, quote?, at? }, opener? }

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only declare non-read-only, non-destructive, non-open-world; the description adds substantive behaviour the annotations do not: a hard 200-per-call cap, cross-test deduplication ('kept once across every test'), and an outbound suppression rule that silently excludes anyone already contacted. It also discloses that an unverified/closed X inbox is 'not counted as reached', which is real silent-skip behaviour. It still doesn't say whether skipped entries are reported back or how partial success surfaces.

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

Conciseness4/5

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

Front-loaded with the action and the cap, then a per-channel glossary — dense and efficient. Some clauses are run-on and the trailing 'Free.' is a fragment whose relevance to the caller is unclear, but almost every sentence carries operational information.

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 two-parameter bulk-insert tool with full schema coverage and no output schema, the description covers eligibility, limits and dedupe well. It stops short of stating what the call returns (added vs skipped counts) or how invalid/duplicate entries within a batch are handled, which matters for a 200-item batch mutation.

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?

Schema coverage is 100%, so baseline is 3, but the description genuinely adds meaning beyond the schema: 'email' must be a published or verified address (never guessed, never catch-all), 'x_dm' only when the inbox is open, 'reddit_dm' is a username, and 'opener' is one line drawn from the person's own post. The 'id' parameter's default (newest open test) is documented in the schema rather than the description, so nothing is lost.

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?

Specific verb plus resource: 'Add people to a Bullseye Test's list, up to 200 a call'. The scope and per-person payload are unambiguous. It never names a sibling (e.g. bullseye_batch, bullseye_plan, outbound_targets), so the boundary against those is left to inference.

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?

Usage context is implied by the eligibility rules (publicly stated the problem, no one outbound already contacted), but there is no explicit 'use this when X, use bullseye_batch instead' guidance despite many adjacent bullseye_* and outreach_* siblings. 'Free' hints at cost behaviour but not at when to prefer this call.

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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