Reddit Post Composer

Reddit Post Composer

Drafts Reddit posts (top-level submissions), not comments. Comments are reddit-monitor + reddit-reply. This skill writes the thing that shows up in the sub's feed.

Not a daily skill. Invoked when Ed has something genuinely worth posting: a real number, a real failure, a real question where input would move the product forward. If there is no underlying reality, the skill refuses to draft. Fabrication is the one unrecoverable error in subs like r/mcp (which bans AI-generated slop on sight).

Dependencies

1. social-media:social-identity — voice + banned patterns + 30% mention cap
2. commons:brand-voice — tone rules
3. commons:identity — ICP and positioning

The audience list (reports/social/reddit/audience/subreddits.json) must exist. If not, instruct the user to run reddit-audience-finder and abort.

Inputs

Three required inputs from the user:

1. Target subreddit — must be in the audience list at Tier A or Tier B. If the user names a Tier C or Drop sub, refuse and suggest the nearest Tier-A/B alternative in the same bucket.
2. Topic — what Ed actually wants to say, in one or two sentences.
3. Underlying data or experience — the real thing behind the post. One of:
   • Numbers we measured (downloads, sessions, blocks, latencies)
   • A failure we experienced and diagnosed (not hypothetical)
   • A decision we're actively stuck on and want input on

If input 3 is missing or abstract, refuse to draft. Respond with: "No underlying data — I won't draft a post that's just an opinion framed as expertise. Come back with the number, the failure, or the specific decision."

Step 1: Load subreddit context

From reports/social/reddit/audience/subreddits.json, pull the record for the target sub:

• subscribers, tier, score
• tone, mention_tolerance, key_rules

Also load the cached hot.json from the latest reddit-audience-finder run (or refetch if older than 3 days) and sample the top 10 posts. This is the reference for native format — title length, selftext length, whether links in body are normalised, whether the community prefers data or narrative.

Step 2: Select post type

Pick ONE of three formats. The sub's tone and recent hot posts determine which works.

A) Data Drop

For subs that reward numbers: r/LLMDevs, r/LocalLLaMA, r/mlops, r/devops, r/cybersecurity, r/ClaudeAI.

• Title: surprising number + context, specific. "We ran 10,000 Claude Code sessions through tool-call hooks. Here's what got blocked."
• Body (400–900 words):
  • Setup (2 paragraphs): what we measured, why, the environment
  • Findings (3–5 paragraphs): the numbers, with specifics
  • Interpretation (1–2 paragraphs): what this means, caveats
  • Open question to the sub (1 line): what would you expect to see?
• Links: never in body. If one belongs, first comment with one sentence of context.

B) Lesson Learned

For subs that reward post-mortems: r/ExperiencedDevs, r/devops, r/cto, r/ITManagers, r/sysadmin.

• Title: specific failure. "We shipped a policy hook that blocked 40% of legitimate Claude requests. Here's how we got it wrong."
• Body (500–1,200 words):
  • Context (1–2 paragraphs): what we were trying to do, the setup
  • What we shipped (1 paragraph): concrete, with code or config if relevant
  • What broke (2–3 paragraphs): the failure, how it surfaced, what the telemetry said
  • Why we got it wrong (2 paragraphs): the wrong assumption, not vague "oops"
  • What we changed (1 paragraph): the fix, with the new approach
  • What we're still unsure about (1 paragraph): the honest open problems
• Links: none in body. Sub rules govern first-comment policy.

C) Call for Input

For subs that reward peer consultation: r/cto, r/ExperiencedDevs, r/devops, r/compliance, r/AI_Agents.

• Title: a specific question, not a generic ask. "How are you enforcing tool-call policy for Claude Code across 30+ devs without destroying their flow?"
• Body (300–600 words):
  • Our setup (1 paragraph): team size, current state, constraints
  • What we've tried (1–2 paragraphs): specific approaches, why each fell short
  • Where we're stuck (1 paragraph): the actual open question
  • What we've ruled out (1 paragraph): so respondents don't suggest those
  • The specific input we want (2 lines): not "any thoughts?", but e.g. "has anyone built centralised CLAUDE.md policy with per-repo overrides without the sync pain?"
• Must actually want input. If the answer is already known and the post is a disguised pitch, abort.

Step 3: Apply sub-specific rules

Read the key_rules field from subreddits.json. Apply these enforcement patterns (add new patterns as they appear):

Step 4: Draft

Write the post. Run through anti-sludge gate:

• No em dashes (U+2014) and no en dashes (U+2013) used as sentence punctuation. En dashes in numeric ranges (1,000–5,000 ms) are fine; en dashes replacing an em dash ("we shipped it – and it broke") are not. Grep the draft for both code points before saving.
• No hashtags
• No AI clichés (revolutionize, leverage verb, supercharge, unlock, seamlessly, harness, cutting-edge, next-generation, paradigm shift, disrupt, empower, reimagine, here's what it is and the numbers, the interesting part is, where it gets interesting)
• No sludge openings ("Fellow {X}...", "Wanted to share...", "Hey everyone...")
• No listing bridges ("Here's what's inside:", "The tl;dr:", "Quick rundown:") immediately preceding a bulleted list — write a topic sentence that carries meaning, not a scan-prompt
• No fabricated data
• No generic closers ("Thoughts?", "What do you all think?", "Happy to dig into any of the above", "Let me know what you think", "Curious what others are doing") — every post closes with either a specific named question or nothing. If the post is a data-drop or lesson-learned with no open question, end on the last substantive sentence.
• Vary sentence length aggressively. Every paragraph must contain at least one sentence under 12 words next to at least one sentence over 20 words. Uniform medium-length sentences are the strongest AI-prose tell on r/rust and r/mcp.

Step 4b: Narrative-over-listing discipline

Comma-list enumerations in prose are the second-strongest AI-prose tell after em dashes. Audit every list — in-prose and bulleted — against these rules:

1. Every bulleted list item binds to a mechanism or a stake. A bullet that names a capability ("Analytics: agent usage, token costs, latency") without explaining how it works or what breaks without it is feature-sheet noise. Delete it or rewrite it with the mechanism.
2. Feature-category bullet dumps are banned in the post body. Listing product surface area (e.g. "the repo ships 43 demos across 10 categories: Governance, Analytics, MCP, Agents, Users, Skills, Infrastructure...") reads as a pitch deck and fails r/rust, r/ExperiencedDevs, r/cto, and r/mcp. If the breadth is genuinely relevant, pick the one category that matches the sub and go deep on it.
3. Three-or-more-item comma lists in prose must each earn their place. "We run four checks: scope, secret scan, blocklist, rate limit" is a scan-list. Convert to narrative: "We answer four questions in order. Is the agent's scope allowed to call this tool. Does the payload carry a credential. Is the tool on a blocklist this tenant maintains. Has this session blown its budget." The narrative version is longer and tests better because each item now carries its own stake.
4. Every jargon term gets a plain-English decoder within the same paragraph. Type names, protocol names, algorithm names, and crate names must be followed within the same or next sentence by a phrase that ties the term to a reader concern. ChaCha20-Poly1305 alone is a term drop; ChaCha20-Poly1305, so a captured log file does not hand over the credential is a term that earned its place.

Feature-writer Rule 6 (Technical-Marketing Synthesis) sub-checks 6b (Jargon Payoff), 6d (Feature-to-Outcome Binding), 6i (Plain-English Narrative), and 6j (Natural Flow) apply directly to Reddit post bodies. Load content:feature-writer for the full exemplar if the draft is mechanism-heavy.

Step 5: Mention audit

Count product mentions. Apply tolerance from subreddits.json:

If the draft exceeds the budget, rewrite until it fits. Mention-budget violations are the most common reason posts get removed from governance-adjacent subs.

Step 6: Output

Save to:

reports/social/reddit/drafts/YYYY-MM-DD-{subreddit}-{slug}.md

{slug} is a lowercase-hyphen 3–6 word summary of the post.

File format:

# Reddit Post Draft

**Subreddit:** r/{sub}
**Tier:** A/B | **Mention tolerance:** {n}/5
**Post type:** data-drop | lesson-learned | call-for-input
**Proposed flair:** {if applicable}
**Mention budget used:** {inline}/1 inline, first-comment link: {yes/no}
**Status:** DRAFT — awaiting Ed review

---

## Title

{title}

---

## Body

{body}

---

## First comment (if any)

{one sentence + link, or "none"}

---

## Why this post, this sub, now

Three bullets:
- What signal in the sub triggered this (specific hot thread or recurring question)
- What real data or experience we're drawing from (must be concrete)
- What response we expect (engagement, a specific discussion, or pipeline signal)

---

## Sub-specific rule compliance

Inline checklist — what rule applied, how the draft satisfies it.

- r/{sub} rule: "{rule}" — satisfied by {specific choice in the draft}
- ...

---

## Pre-submit checklist (for Ed)

- [ ] Read 10 most-upvoted posts from this sub in the last 7 days — our draft matches the native format
- [ ] Zero AI-clichés, em dashes (U+2014), punctuation en dashes (U+2013), hashtags (anti-sludge gate passed)
- [ ] Narrative-over-listing audit passed (Step 4b): no feature-category bullet dumps, every list item binds to mechanism or stake, every jargon term has a plain-English decoder
- [ ] Every paragraph contains at least one short (<12 word) and one long (>20 word) sentence
- [ ] Closer is a specific named question or the last substantive sentence — not "Thoughts?" / "Happy to dig into..." / "Curious what others think"
- [ ] Every numeric claim is real (not fabricated)
- [ ] Mention budget respected per this sub's tolerance
- [ ] Link (if any) placed in first comment only
- [ ] Appropriate flair selected
- [ ] If r/rust and post is project/showcase, at least one fenced code block present
- [ ] If r/selfhosted and project <3 months old, target is the megathread not the main feed
- [ ] If r/ClaudeAI and this is a comparison, our own evaluation data is included

---

## Expected log entry (H-###)

If this post is shipped as a seeded hypothesis, log format:

- **Channel:** reddit / r/{sub}
- **Action:** top-level post, type={type}
- **Hypothesis:** {metric} will rise from {baseline} to {target} within {window} days
- **Metric:** {specific metric to watch}
- **Window end:** {date}

(Ed fills in the actual hypothesis and metric when queuing the post in `commons:marketing-hypothesis-ledger`.)

What the composer refuses to do

• Draft a post without real underlying data or experience
• Submit to a sub below Tier B
• Exceed the mention budget for the sub's tolerance
• Produce identical content for multiple subs (every draft is native to its sub)
• Generate "thought leadership" with no verifiable content behind it
• Write in a voice that doesn't match the sub (e.g. casual ClaudeAI voice in r/cto)

Quality checklist

• Subreddit loaded from audience list (Tier A or B only)
• Real data/experience provided by user (not abstract)
• Post-type matches sub culture per Step 2 table
• All applicable sub-specific rules enforced per Step 3 table
• Anti-sludge gate passed (Step 4)
• Narrative-over-listing audit passed (Step 4b)
• Mention budget respected per tolerance (Step 5)
• Draft file saved with correct date, sub, slug
• Pre-submit checklist populated for Ed's review