social-audit

social-audit is a skill for Claude Code from inklate/social-skills. It costs 181 tokens per session (1,847 once invoked), scanned A, original, MIT.

A review guide for a social profile and recent posts on LinkedIn, X, Instagram, Facebook, Threads, or Bluesky. It compares what you published with your stated goals, topics, audience, and posting frequency.

In plain words
What is it for?
Use it to review a profile, recent posts, posting consistency, and performance, then produce a prioritized list of problems and three suggested actions.
Why use it?
It helps identify gaps instead of relying on guesses about why an account is not growing. The review also makes clear what cannot be judged without information such as views or impressions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the social-skills plugin — 14 skills shipped together

Good fit Use it to review a profile, recent posts, posting consistency, and performance, then produce a prioritized list of problems and three suggested actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/inklate/social-skills/social-audit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add inklate/social-skills --skill social-audit
Clone the repo
git clone --depth 1 https://github.com/inklate/social-skills

Made for: Claude Code.

Or install social-skills, the plugin that ships this one along with the rest of its 14 skills.

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 social-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/inklate/social-skills/social-audit/github.svg)](https://agentmods.dev/skills/inklate/social-skills/social-audit)
Your own site
<a href="https://agentmods.dev/skills/inklate/social-skills/social-audit"><img src="https://agentmods.dev/badge/skills/inklate/social-skills/social-audit/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for social-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/inklate/social-skills/social-audit"><img src="https://agentmods.dev/badge/skills/inklate/social-skills/social-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 181 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,847 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00181 $0.01847
Opus 5 $0.00090 $0.00924
Sonnet 5 $0.00036 $0.00369
Haiku 4.5 $0.00018 $0.00185

Measured 13d ago against content hash 6b523586776f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

social-audit 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 13d 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/social-audit/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audit the profile and content history the user gives you against their stated goals, and hand back a prioritized gap list with a 3-move action plan.

Context

Read social-context.md at the project root (also check .agents/social-context.md) for the ## Goals, ## Pillars, ## Audience, and ## Cadence sections — the audit measures reality against these, so they matter more here than in any other task. If it's missing, offer to run the social-context skill first, but don't block — ask 2–3 quick inline questions and proceed:

  • What's the goal — leads, audience growth, hiring, authority?
  • What pillars did you intend to post about?
  • What cadence did you intend to keep?

Workflow

  1. Collect the evidence. Ask the user to paste what they have:
    • recent posts, text plus dates — ideally the last 20–30;
    • the bio/profile text, the link, and what's pinned;
    • any numbers they can report: follower trend, typical impressions/likes, their best and worst post. Work only from what's pasted. State clearly up front what you cannot assess without more — e.g. "without impression data I can score your hooks but not your reach; paste your top and bottom 5 posts by impressions if you have them." Never fill an evidence gap with a guess.
  2. Score posting consistency. From the post dates, compute actual posts-per-week and compare to the intended cadence from context. Flag gaps longer than 2× the intended interval, and flag clustering — five posts in three days, then two weeks of silence, is not a 2.5/week cadence. Check this dimension first: consistency gaps explain "flat" more often than content quality does, and every other score is noisy until cadence is stable.
  3. Score pillar balance. Tag each pasted post with its pillar, or "off-pillar" if it fits none. Report the actual distribution against the intended pillars, with counts. Be specific and honest: "your last 12 posts are all pillar #1" — never soften it to "consider diversifying your content". Both failure modes are findings: single-pillar collapse and off-pillar drift.
  4. Score hook quality. Take the first line of each of the last N posts (N = what they pasted, cap 20) and score each 0–2:
    • 0 — label or throat-clearing: "Some thoughts on hiring." / "I've been meaning to write this."
    • 1 — clear topic, no tension: "How we run our onboarding."
    • 2 — specific claim, tension, or curiosity gap that survives truncation: "Our onboarding had a 60% drop-off at step 2. One email fixed it." Report the average, then quote the worst three verbatim with rewrites — the rewrites teach more than the scores do. Then check fit: flag any hook aimed at the wrong reader for the ## Audience in context — a strong hook for the wrong audience still misses.
  5. Score format mix. Count the formats used — text post, thread, carousel/document, image, video/Reel — against what the platform rewards and what the goal needs. Two failure modes, both findings: one-format monoculture, and format-chasing where nothing is tried twice so nothing can be learned.
  6. Read the engagement pattern — from their numbers only. If the user reported numbers, look for the shape:
    • which pillar and format overlap their best posts;
    • whether engagement concentrates in a few spikes or sits flat across everything;
    • replies-vs-likes ratio if known — replies signal resonance, likes-only signals passable-but-skippable. If they reported nothing, write "unknowable from pasted data" for this dimension and move on. Do not infer engagement from post text.
  7. Audit the profile itself. A growth problem is often a conversion problem — people arrive from a good post and bounce off a vague bio. Check line by line:
    • first line of the bio: does it name the audience from ## Audience and the offer from ## Positioning — who it's for and what they get — or is it a job title and three emoji?
    • credibility: any evidence — numbers, names, track record?
    • the link: present, working destination described, matched to the goal?
    • pinned post: their best converter, or just their newest?
    • profile photo and banner: present and legible at feed size, as described?
  8. Diagnose against the goal. Connect the findings to the stated goal, not to generic best practice: flat followers + solid consistency + weak hooks is a top-of-funnel problem; good reach + no leads is a bio/CTA problem; erratic cadence means nothing else is measurable yet — fix that before optimizing anything. Name the single biggest lever explicitly, in one sentence.
  9. Build the gap list. Every finding as one line: severity (high/med/low), the evidence (a quote, count, or date range from their own data), and the fix. Order by expected impact on their goal, not by ease of fixing.
  10. Write the 3-move action plan. Exactly three moves, biggest lever first, each concrete enough to start this week — "rewrite your bio's first line to name the audience; here's a draft", not "improve your profile". Wherever a move has a draft or example, include it inline.

Read the full file on GitHub · 91 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 13d ago First seen · 91 lines · 181 tokens per session scan A 6b523586776f

Subscribe to this mod's changes

social-audit is a skill published in the GitHub repository inklate/social-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 181 tokens to every session and 1,847 once invoked, about $0.0009 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 2026-08-31.

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