assemble-document

assemble-document is a skill for Claude Code from indranilbanerjee/socialforge. It costs 90 tokens per session (782 once invoked), scanned A, original, MIT.

A skill that packages an approved month of social media posts into one structured JSON delivery manifest, a machine-readable handoff file.

In plain words
What is it for?
Use it to assemble a monthly calendar, group posts by week, include approval data, and produce the final delivery document.
Why use it?
It gathers post copy, creative files, platform versions, statuses, and schedule details into a consistent client or publishing handoff.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the socialforge plugin — 20 skills, 25 commands, 5 agents shipped together

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add indranilbanerjee/socialforge
Claude Code
/plugin install socialforge

Made for: Claude Code.

Or install socialforge, the plugin that ships this one along with the rest of its 20 skills, 25 commands, 5 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for assemble-document

README.md
[![agentmods](https://agentmods.dev/badge/skills/indranilbanerjee/socialforge/assemble-document.svg)](https://agentmods.dev/skills/indranilbanerjee/socialforge/assemble-document)
Your own site
<a href="https://agentmods.dev/skills/indranilbanerjee/socialforge/assemble-document"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/socialforge/assemble-document.svg" alt="Measured on agentmods" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 782 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.00782
Opus 5 $0.00045 $0.00391
Sonnet 5 $0.00018 $0.00156
Haiku 4.5 $0.00009 $0.00078

Measured 6d ago against content hash f4176318576c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

assemble-document scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/assemble-document/SKILL.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/socialforge:assemble-document — Document Assembler

Create the final delivery manifest — a structured JSON file describing the complete monthly calendar, its posts, copy, and metadata. The manifest is the deliverable this skill produces; a formatted DOCX is a manual/optional step downstream (see below).

Manifest Structure

assemble_docx.js emits these sections into the JSON manifest:

  1. Title block (brand name, month, generation timestamp)
  2. Monthly overview (post count, platform breakdown, tier distribution, content-type distribution)
  3. Weekly sections:
    • For each post: post id, date, title, tier, platforms, content type, copy option A, visual direction, creative mode, status
  4. Publishing schedule (date, day of week, post id, title, platforms)

Process

  1. Load calendar-data.json and status-tracker.json for the brand + month
  2. Group posts by week and merge in each post's tracked status and creative mode
  3. Build the manifest structure
  4. Save to ${CLAUDE_PLUGIN_DATA}/socialforge/output/{brand}/{month}/FINAL/00-Calendar-Document/{brand}-{month}-calendar.json (falls back to ~/socialforge-workspace/output/... when ${CLAUDE_PLUGIN_DATA} is unset)

AI-assistance note (delivery manifest)

Read ai_disclosure from brand-config.json (missing block = {"mode": "claude-surfaces", "text": null}) and decide whether the manifest carries the AI-assistance note:

  1. Run python ${CLAUDE_PLUGIN_ROOT}/scripts/detect_surface.py --mode {mode} — its disclosure_applies field IS the decision. Fail-safe: an uncertain surface applies the note in claude-surfaces mode; skipping requires an AFFIRMATIVE non-Claude fingerprint. Never override the script's answer.
  2. When it applies, add to the manifest metadata: "ai_assistance_note": "Creative produced with AI assistance under human review and brand approval gates." (or the brand's custom text verbatim). The default wording is vendor-neutral and claims only the review this pipeline actually performs — every post passed the approval chain.
  3. Record the decision either way: "disclosure": {"applied": true|false, "mode": ..., "surface": ...} in the manifest — an unapplied note is a recorded choice, not an omission.
  4. Remind the user at handoff: platform-native AI-content labels (Instagram/TikTok/YouTube toggles) are the right place for per-post disclosure — flag which posts used AI generation so whoever publishes can set them.

Read the full file on GitHub · 45 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 45 lines · 90 tokens per session scan A f4176318576c

Subscribe to this mod's changes

assemble-document is a skill published in the GitHub repository indranilbanerjee/socialforge (36 stars, last pushed 19d ago), licensed MIT. It adds 90 tokens to every session and 782 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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