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by com.nilyo
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LinkedIn: Reply to comment

linkedin_reply_to_comment
Destructive

Reply DIRECTLY to one exact LinkedIn comment, not create a new top-level comment. Required chain from human reference: resolve post -> post.id -> list comments -> comment.id -> optionally read replies -> reply. Post ID: Exact provider post id; LinkedIn commonly uses a preformatted/base64-style post ID. Obtain with: linkedin_search_posts -> result.id; linkedin_list_user_posts -> result.id; instagram_list_user_posts -> result.id Never pass: post text, author user ID, URL unless a resolver tool explicitly accepts it. Comment ID: Exact comment id scoped to the identified post. Obtain with: linkedin_list_post_comments(post_id) -> comment.id; instagram_list_post_comments(post_id) -> comment.id Never pass: comment text, post_id.

Input Schema

NameRequiredDescriptionDefault
textYesFinal reply text explicitly requested/approved by the user. LinkedIn Classic mentions belong in text: @ followed by the resolved person's Classic ACo... ID or the company's numeric ID (for example @1441). Resolve people with linkedin_get_profile_from_url/linkedin_resolve_person and companies with linkedin_resolve_company/linkedin_search_companies; disambiguate every target before publishing. Never use a display name, profile URL, company slug, URN, Sales Navigator or Recruiter ID as a mention. Example after resolving both targets: 'Thanks @ACo_RESOLVED_MEMBER for working with @1441.' The API replaces each token with the target's name and mention metadata; no separate mentions field is needed. Approve the final text and mentioned identities before the write; never retry an ambiguous write automatically.
post_idYesExact post ID from post search/list. Post ID: Exact provider post id; LinkedIn commonly uses a preformatted/base64-style post ID. Obtain with: linkedin_search_posts -> result.id; linkedin_list_user_posts -> result.id; instagram_list_user_posts -> result.id Never pass: post text, author user ID, URL unless a resolver tool explicitly accepts it.
account_idNoOptional Nilyo connection ID (unipile_account_id from list_connected_accounts). Omit when the user has one account for this provider. When several exist, Nilyo never guesses: list them (display name, identifier, provider user ID), choose the one the user named or ask, and pass its ID here.
comment_idYesExact comment ID from comments of the resolved post. Comment ID: Exact comment id scoped to the identified post. Obtain with: linkedin_list_post_comments(post_id) -> comment.id; instagram_list_post_comments(post_id) -> comment.id Never pass: comment text, post_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / text / description
      Previous value: -"Final reply text explicitly requested/approved by the user."New value: +"Final reply text explicitly requested/approved by the user. LinkedIn Classic mentions belong in text: @ followed by the resolved person's Classic ACo... ID or the company's numeric ID (for example @1441). Resolve people with linkedin_get_profile_from_url/linkedin_resolve_person and companies with linkedin_resolve_company/linkedin_search_companies; disambiguate every target before publishing. Never use a display name, profile URL, company slug, URN, Sales Navigator or Recruiter ID as a mention. Example after resolving both targets: 'Thanks @ACo_RESOLVED_MEMBER for working with @1441.' The API replaces each token with the target's name and mention metadata; no separate mentions field is needed. Approve the final text and mentioned identities before the write; never retry an ambiguous write automatically."
  2. Changed1 schema field changed
    • changedInput schema / properties / post_id / description
      Previous value: -"Exact post ID from post search/list. Post ID: Exact provider/Unipile post id; LinkedIn commonly uses a preformatted/base64-style post ID. Obtain with: linkedin_search_posts -> result.id; linkedin_list_user_posts -> result.id; instagram_list_user_posts -> result.id Never pass: post text, author user ID, URL unless a resolver tool explicitly accepts it."New value: +"Exact post ID from post search/list. Post ID: Exact provider post id; LinkedIn commonly uses a preformatted/base64-style post ID. Obtain with: linkedin_search_posts -> result.id; linkedin_list_user_posts -> result.id; instagram_list_user_posts -> result.id Never pass: post text, author user ID, URL unless a resolver tool explicitly accepts it."
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, but the description adds substantial behavioral context: it explains that mentions are resolved via @ tokens and replaced by the API, that targets must be disambiguated before publishing, that final text and identities must be approved, and that ambiguous writes should never be retried automatically.

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 front-loaded with the core purpose and organized into Post ID and Comment ID sections, but it duplicates much of the schema's property descriptions, making it somewhat longer than necessary.

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 lack of an output schema, the description covers the full workflow (ID resolution, optional reply reading, mention resolution, approval before write) and is complete enough for an agent to invoke the tool correctly. Annotations handle the safety profile, and the schema covers parameters.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all parameters including the mention syntax for text and ID sources. The description largely repeats this information rather than adding new parameter-level meaning, so the baseline 3 applies.

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?

States a specific verb (reply) and resource (one exact LinkedIn comment) and explicitly contrasts with creating a new top-level comment, so the agent can distinguish it from siblings like linkedin_comment_on_post without opening the schema.

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?

Provides a required resolution chain (resolve post -> post.id -> list comments -> comment.id -> optionally read replies -> reply) and clearly says not to create a new top-level comment. It also names the tools to obtain post and comment IDs, giving explicit when-to-use and how-to-proceed guidance.

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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