agentleFS
priyanshu-aryapriyanshu-arya/LinkedIn_Automation/.claude/skills/draft-reply/SKILL.md

draft-reply

Skill0 starsChanged 58 days agoMITView on GitHub

Use when the user wants to draft a reply to a LinkedIn comment, wants replies drafted for an entire post's comment thread at once, or explicitly invokes /draft-reply. Given a single pasted comment, drafts one reply. Given a pasted full thread export, sweeps every top-level comment and reply, filters out low-value ones, and drafts the rest in one batch — correctly attributing who each reply is addressed to across LinkedIn's 2-level thread flattening. Input follows REQUIREMENTS.md §27 (pasted text primary; a post URL alone is not reliable). Never posts anything itself — output is copy-ready text for manual posting, and no vault artifact is created.

6 other projects use a version of this.

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The file

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We split this skill into the rules it gives an agent

14 rules. 0 are common, 7 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If it's ambiguous which mode applies (e.g.

    line 29
  2. Very specific:

    If no such @mention is present, replied_to defaults to the top-level comment's author (the reply is assumed to address the thread starter, …

    line 49
  3. Very specific:

    Never guess a replied_to target beyond these two rules — if the text is ambiguous even with the @mention convention, say so rather than …

    line 52
  4. Distinctive:

    When drafting, label every reply output as:

    line 56
  5. Distinctive:

    Keep everything else — including a short-but-substantive disagreement, a real question, a correction, or a personal anecdote tied to the …

    line 84
  6. Distinctive:

    Always report which comments were skipped and why: Never silently drop a comment from the output — the skipped-comment log is a required …

    line 88
  7. Very specific:

    Read Content-Learnings/voice-guide.md in full, fresh — never rely on a cached memory of it.

    line 97
  8. Very specific:

    Read Content-Learnings/voice-guide.md in full, fresh.

    line 110
  9. Very specific:

    Never auto-post a reply, and never imply one was posted — there is no comment-posting API anywhere in this repo, same limitation as …

    line 126
  10. Distinctive:

    Never fabricate a comment's content, author, or thread structure beyond what was actually pasted.

    line 130
  11. Distinctive:

    Never invent context about the original post beyond what the user actually gave.

    line 133
  12. Very specific:

    Every drafted reply follows Content-Learnings/voice-guide.md's tone — conversational, direct, no AI-writing tells.

    line 135
  13. Distinctive:

    Never silently drop a low-value comment from the sweep report — always state that it was skipped and why.

    line 137
  14. Very specific:

    No vault artifact: no Draft Note, no Drafts/ entry, no approval- pipeline lifecycle, for either mode.

    line 139

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Reply Handler

Drafts replies to comments on the user's own (or anyone else's) LinkedIn post — either one comment at a time, or a full-thread sweep. Same lightweight, mostly ephemeral shape as Comment Drafter (/draft-comment): not part of the Drafts/ approval pipeline. Output is copy-paste text in the response; there is no Draft Note, no vault schema, no file write.

Reading third-party post/comment content: see REQUIREMENTS.md §27 — pasted text is the primary, reliable input; a post URL is optional metadata only, and a WebFetch attempt on it is best-effort convenience, never ground truth.

Modes

  • Single-reply — the user pastes one comment (optionally plus the original post's text/topic for context) and wants one reply drafted.
  • Sweep — the user pastes a full thread export (all top-level comments and their replies, as copied from the post) and wants a reply drafted for every comment/reply worth answering, in one batch. A post URL may come along as best-effort/reference-only metadata per §27 — never relied on to reconstruct thread content that wasn't actually pasted.

If it's ambiguous which mode applies (e.g. a short paste with no visible reply structure), ask, or default to single-reply for one comment / sweep for anything with multiple comments.

Flattening-handling design (sweep mode)

LinkedIn's UI only nests one level deep: a reply to a reply gets flattened into the same top-level-reply list, with LinkedIn auto-inserting an "@Name" prefix on the reply's text to show who it was actually meant for — it is not real nesting, and the export the user pastes will preserve that flattened, one-level shape.

On parse, build a flat list per top-level comment:

{author, text, replied_to}
  • replied_to is inferred from an explicit "@Name" at the start of a reply's text (LinkedIn's own flattening marker).
  • If no such @mention is present, replied_to defaults to the top-level comment's author (the reply is assumed to address the thread starter, not some other repliers further down).
  • Never guess a replied_to target beyond these two rules — if the text is ambiguous even with the @mention convention, say so rather than picking a guess silently.

When drafting, label every reply output as:

Reply to [Author] (responding to [X] in this thread)

and have the drafted reply text itself open by naming or otherwise clearly addressing that specific person's point — never a generic reply that could float under any comment in the thread. If two different people replied to two different targets within the same top-level thread, keep their drafted outputs visually grouped under that thread for one scan-through, but each still carries its own explicit target label so nothing gets misattributed when the user copies them back individually.

Low-value filter (sweep mode only)

Single-reply mode always drafts what's asked — the filter only runs in sweep mode, to avoid wasting a drafted reply on a comment not worth answering. Skip, and log as skipped with a reason, anything that is:

  • Pure emoji/reaction-only — "🔥🔥", "👏", no words.
  • Generic praise with zero specific reference to post content — "Great post!", "So true", "Well said" and nothing else.
  • Off-topic self-promotion/spam — an unrelated link drop, "check out my profile/product".
  • A near-duplicate of a comment already answered earlier in the same thread — same point, no new angle.
  • A tag/mention with no added content — "@friend check this out" and nothing else.

Keep everything else — including a short-but-substantive disagreement, a real question, a correction, or a personal anecdote tied to the post, even if brief. When in doubt, keep it rather than skip it.

Always report which comments were skipped and why. Never silently drop a comment from the output — the skipped-comment log is a required part of every sweep report.

Process

Single-reply mode

  1. Take the pasted comment, plus the original post's text/topic if given, per §27 (pasted text primary; a URL alone is not reliable).
  2. Read Content-Learnings/voice-guide.md in full, fresh — never rely on a cached memory of it.
  3. Draft one reply: short, specific to what the comment actually said, in the user's own voice, no throat-clearing, no generic filler.
  4. Output as copy-ready text.

Sweep mode

  1. Ingest the pasted full thread export.
  2. Parse into top-level comments plus attributed replies per the flattening design above — build the {author, text, replied_to} list for each top-level thread.
  3. Apply the low-value filter to every comment and reply, logging what's skipped and why.
  4. Read Content-Learnings/voice-guide.md in full, fresh.
  5. Draft a reply for each surviving comment/reply, each carrying its explicit "Reply to [Author] (responding to [X])" addressee label.
  6. Present the full batch grouped by original top-level thread, so the user can scan one thread at a time.
  7. Report counts: total parsed / filtered out / drafted.

Report back

  • The drafted repl(ies) as copy-ready text.
  • In sweep mode: each reply labeled with who it's addressed to, grouped by top-level thread; the skipped-comment log with reasons; and the parsed/filtered/drafted counts.

Hard rules

  • Never auto-post a reply, and never imply one was posted — there is no comment-posting API anywhere in this repo, same limitation as /draft-comment (REQUIREMENTS.md §27, §33). Output is always copy-paste text for manual posting.
  • Never fabricate a comment's content, author, or thread structure beyond what was actually pasted. If the pasted thread is ambiguous or incomplete, say so rather than inventing the missing shape.
  • Never invent context about the original post beyond what the user actually gave.
  • Every drafted reply follows Content-Learnings/voice-guide.md's tone — conversational, direct, no AI-writing tells.
  • Never silently drop a low-value comment from the sweep report — always state that it was skipped and why.
  • No vault artifact: no Draft Note, no Drafts/ entry, no approval- pipeline lifecycle, for either mode.

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