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avivancos
by avivancos

import_from_url_findings

Import confirmed LinkedIn, GitHub, or portfolio data into your active profile, recording the source URL for provenance. Run after previewing and confirming the extracted fields.

Instructions

Apply client-LLM-extracted structured fields (LinkedIn/GitHub/portfolio) to the active profile, recording the source url for provenance. Call ONLY after preview_url_import + human CONFIRM — this tool writes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
fieldsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that this tool writes, records provenance, and requires human confirmation, which is helpful context. However, it fails to clarify whether the mutation merges or overwrites existing fields, whether it is reversible, or what happens to previously stored fields—important behavioral gaps for a write 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, front-loaded with the main action and followed by a necessary usage warning. Every word earns its place; no redundant or vague filler.

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?

The description covers the primary purpose, the required sequence, and warns about the write nature. Given the output schema exists, return values don't need elaboration. However, it omits details about how existing profile fields are affected (merge vs replace), which is a notable gap for a tool that modifies an active profile.

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 0%, so the description must compensate. It does by explaining that 'url' is the source URL for provenance and 'fields' are client-LLM-extracted structured fields, giving examples (LinkedIn/GitHub/portfolio). While it doesn't specify the internal field object structure, it adds meaningful semantic context beyond the raw parameter names.

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?

Description clearly states the action ('Apply client-LLM-extracted structured fields'), the target ('the active profile'), and the additional provenance behavior ('recording the source url'). It also distinguishes this write tool from the sibling preview_url_import by explicitly saying this tool writes and must be called after preview.

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?

The description gives an explicit usage rule: 'Call ONLY after preview_url_import + human CONFIRM — this tool writes.' This clearly indicates when to use it and when not to (before preview/confirmation), effectively naming the alternative tool and the required sequence.

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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