HeyLead

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brand_strategy

Destructive

Audit your LinkedIn profile, generate a personalized brand strategy, and execute actions like headline rewrites and content topics to attract more leads.

Instructions

Analyze and improve your LinkedIn personal brand to drive more leads.

Audits your profile, generates a personal brand strategy, executes
actions (post topics, headline rewrites, engagement targets), and
tracks improvement over time.

Args:
    action: What to do:
        "analyze" — Full profile audit with scored areas and issues
        "plan"    — Generate a 4-week brand strategy with content calendar
        "execute" — Execute the next recommended action from your plan
        "progress" — Show before/after metrics and completed actions
        "upload_photo" — Upload a profile photo (provide file_path or base64 data)
        "upload_cover" — Upload a cover/banner photo (same input as upload_photo)
        "set_link" — Set custom CTA link on profile (pass URL via focus param)
        "set_headline" — Set the headline to exact text (pass the headline via focus)
        "set_summary" — Set the About section to exact text (pass the text via focus).
            Use these two when the user has already decided the wording; "execute"
            and "makeover" write model-generated copy instead.
        "set_photo_library" — Folder of the user's own photos that brand-calendar
            posts may attach (pass the folder path via focus; "off" clears it).
            Files named "NNN - what it shows.jpeg"; personal or family subfolders
            are never used. Local posting only: a cloud-owned seat posts text only.
    focus: Focus area for analyze/plan ("headline", "summary", "content", "engagement", ""),
        URL string for set_link, the literal text for set_headline / set_summary,
        or the folder path for set_photo_library.
    photo: File path or base64-encoded image for upload_photo / upload_cover actions.

Input Schema

TableJSON Schema

Name	Required	Default
`focus`	No
`photo`	No
`action`	No	analyze

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.375Sep 18, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already mark the tool as mutating, destructive, and open-world; the description adds meaningful behavioral context by specifying exactly which actions write to the profile and by documenting the local-posting limitation and cloud-owned-seat text-only constraint. It does not discuss reversibility or permissions, but the action list makes the mutating behavior clear.

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?

The description is long but justified by the breadth of actions. It is front-loaded with the core value proposition and organized as an Args block with useful details like folder naming conventions and cloud-vs-local behavior. The dangling 'makeover' mention adds minor confusion but does not undermine the overall structure.

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?

For a complex multi-action tool with a bare input schema, the description covers almost everything an agent needs: action semantics, focus/photo reuse, folder naming rules, and an important posting caveat. It does not mention prerequisites like a connected LinkedIn profile or fully define the unreferenced 'makeover' flow, but output schema presence reduces the need for return-value detail.

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?

With 0% schema description coverage, the description carries the full burden of parameter meaning and mostly succeeds: action is documented as an enum-like set of behaviors, focus is polymorphically defined per action, and photo is explained as a file path or base64 value. The unexplained reference to a 'makeover' action that is not defined in the action list is a notable gap.

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 states a specific mission: analyze and improve the user's LinkedIn personal brand to drive leads. It enumerates concrete action modes such as analyze, plan, execute, and progress, making the tool's scope clear. However, it does not explicitly differentiate itself from nearby sibling tools like setup_profile or create_post.

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?

The description implies use for personal-brand strategy work and provides useful internal routing guidance, such as using set_headline/set_summary when the user already decided the wording versus model-generated copy. It never names alternatives or states when NOT to use this tool, leaving tool-level boundaries to inference.

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