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log_outreach

Record sent outreach with recipient, channel, and variant to build a ledger. Enables prior-contact checks and reply-rate stats while surfacing existing history with that target.

Instructions

Record an outreach message the user actually SENT. Call this when the user says they sent a message ("I sent it", "log this outreach").

The stored ledger replaces a manual sent-log: it powers prior-contact checks, reply-rate stats, and the reflection loop that learns what works. The response includes any prior contact with the same target — surface that to the user if present.

Args: target_url: LinkedIn profile URL (or email address) of the recipient. message: The exact message text that was sent. target_name: Recipient's name (optional but recommended). company: Recipient's company (optional). channel: "dm" | "email" | "other" (default "dm"). variant: Which draft variant was sent: "warm" | "direct" | "follow-up" | free text. hook_type: Opening hook used: "question" | "statement" | "story" | "stat" | "commonality" | free text. Used for reply-rate breakdowns. notes: Anything worth remembering about this send (optional).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNo
channelNodm
companyNo
messageYes
variantNo
hook_typeNo
target_urlYes
target_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool writes to a ledger, that the ledger powers downstream analytics, and that the response includes prior contact history with the same target. This is substantive behavioral context beyond the schema.

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 well-organized: trigger phrasing first, then ledger purpose, then a concise reference-style Args list. There is no filler, and every sentence adds decision-relevant information.

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

Completeness5/5

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

Given the tool's moderate complexity, the description covers invocation triggers, parameter semantics, behavioral side effects, and response expectations in a compact way. The output schema exists, so the description does not need to detail the full return type, and it even instructs the agent to surface prior-contact matches from the response.

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

Parameters5/5

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

The schema has 0% description coverage, but the description fully compensates with an Args block that explains every parameter, including valid enum values for channel, variant, and hook_type, plus optionality and defaults. This adds significant meaning beyond the raw schema titles.

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 opens with a specific verb and resource: 'Record an outreach message the user actually SENT.' It clarifies the tool's exact scope and even gives example user phrasings that should trigger it, which distinguishes it from outcome-related tools like record_outcome.

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

Usage Guidelines4/5

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

It explicitly states when to call the tool: 'Call this when the user says they sent a message.' It also explains the broader purpose of the stored ledger, giving clear context. It stops short of naming alternatives or saying when not to use it, so it misses the top score.

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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