Install
$ agentstack add skill-analystacademy-claude-skills-postready ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Post-Ready Pipeline
End-to-end content pipeline. Source material in → publish-ready LinkedIn posts out.
Runs four skills in sequence, automatically. No checkpoints. No menu. No asking which steps to run.
- content — draft 3–4 posts from the source
- factcheck — verify factual claims (Standard tier, no tier picker)
- hatchet — tighten each post
- ask-hr — HR-screen each post and apply rewrites for anything flagged
> Setup note: This skill orchestrates four other skills (content, factcheck, hatchet, ask-hr). All four must be installed. The path references below assume they live under your skills directory (e.g. ~/.claude/skills/content/SKILL.md) — adjust if yours are different.
Step 1: Generate the drafts (content)
Read the content SKILL.md and follow its instructions to:
- Identify and ingest the source content (pasted text, PDF, URL, email, newsletter, etc.)
- Find the best 3–4 angles
- Draft full-length posts in the user's voice (using the
postskill)
Two important deviations from content's normal flow:
- Skip
content's internal factcheck step. This pipeline runs factcheck centrally in Step 2 — don't double up. - Do not "present" the posts yet.
contentnormally ends by presenting finished drafts to the user. Here, treat the drafts as intermediate output and pass them to Step 2.
Step 2: Fact-check the drafts (factcheck — Standard tier)
Read the factcheck SKILL.md and run the Standard tier on every post that contains:
- Statistics or numbers
- Named figures, organizations, or surveys
- Specific historical, scientific, or attributed claims
Skip the tier picker entirely. Don't ask which tier — always Standard.
For each ❌ Incorrect or ⚠️ Partially correct finding, apply the suggested fix directly into the draft. Keep a one-line note per fix for the final summary (e.g. "Post 2: corrected '85% of jobs in 2030' → 'a widely cited but unsourced claim removed'").
If a post has no checkable claims, skip the search and note "no claims to check" in the pipeline notes.
Step 3: Tighten each post (hatchet)
Read the hatchet SKILL.md and run hatchet on each (now factchecked) post.
- Default target: roughly 50% reduction
- If a post is already tight, just clean it up — don't over-cut
- Preserve the user's voice and the sharp opening line
- Do not collapse the post into a single paragraph if the original used line breaks for rhythm
The hatchet output is intermediate — feed it into Step 4, don't present it yet.
Step 4: HR-screen each post (ask-hr)
Read the ask-hr SKILL.md and run an HR review on each tightened post.
For each post, decide based on the verdict:
| Verdict | Action | |---|---| | ✅ Clear or 🟢 Low Risk | Keep the post as-is from Step 3 | | 🟡 Moderate Risk | Use the Full Rewrite from ask-hr as the final version | | 🔴 High Risk | Use the Full Rewrite from ask-hr as the final version, flag prominently in pipeline notes |
Keep HR notes brief — name the issue and severity, one or two lines per flagged post. Don't include the full risk-score table in the final output.
Step 5: Present the final posts
Format the response exactly like this:
📦 Post-Ready: [N] posts
Post 1 — [angle type]
[Final post text — factchecked, tightened, HR-cleared]
Post 2 — [angle type]
[Final post text]
(repeat for each post)
🔧 Pipeline notes
Factcheck: [one line per fix applied, or "All claims verified" / "No checkable claims"]
Hatchet: [rough reduction summary, e.g. "Posts trimmed ~40–55%" or "All posts already tight, light cleanup only"]
HR: [any flags caught and the rewrite applied, or "All posts cleared"]
End by asking which (if any) the user wants to adjust further.
What NOT to do
- Do NOT pause for approval between steps — the whole point of
postreadyis end-to-end automation - Do NOT show intermediate drafts (raw, factchecked-but-not-trimmed, etc.) — only the final versions
- Do NOT skip any of the four steps on any post, even ones that look "obviously fine"
- Do NOT use a different factcheck tier — always Standard
- Do NOT over-cut tight posts in the hatchet step
- Do NOT open posts with newsletter meta-framing ("This week's newsletter…", "I read a PDF that…") — same rule as
content - Do NOT include the full
ask-hrrisk-score table or the fullfactcheckper-claim report in the final output — keep pipeline notes brief
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: analystacademy
- Source: analystacademy/claude-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.