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.
npx skills add Mora-AI-Content-Studio/mora-claude-plugin --skill content-performance-auditgit clone --depth 1 https://github.com/Mora-AI-Content-Studio/mora-claude-pluginWrote 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.
[](https://agentmods.dev/skills/mora-ai-content-studio/mora-claude-plugin/content-performance-audit)<a href="https://agentmods.dev/skills/mora-ai-content-studio/mora-claude-plugin/content-performance-audit"><img src="https://agentmods.dev/badge/skills/mora-ai-content-studio/mora-claude-plugin/content-performance-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.
<a href="https://agentmods.dev/skills/mora-ai-content-studio/mora-claude-plugin/content-performance-audit"><img src="https://agentmods.dev/badge/skills/mora-ai-content-studio/mora-claude-plugin/content-performance-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00089 | $0.01101 |
| Opus 5 | $0.00044 | $0.00550 |
| Sonnet 5 | $0.00018 | $0.00220 |
| Haiku 4.5 | $0.00009 | $0.00110 |
Grade A, and why
content-performance-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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Performance Audit
Turn Mora's raw post history and engagement data into a short, actionable brief instead of a data dump. A user asking "how is my content doing" wants a verdict and a next move, not two JSON blobs pasted back at them.
Scope
Ground any "what to post next" answer in this account's actual history rather than generic social media advice — that is the whole point of this skill over just writing from best practice.
Procedure
- Call
get_post_performancefirst (default limit is fine unless the user asks for a longer history) to get this account's best-performing published posts ranked by summed engagement (likes + comments + shares + saves). - Call
list_poststo see the fuller picture — drafts, scheduled, and recently published posts across all statuses. This surfaces volume and cadence thatget_post_performancealone cannot, since it only returns published posts with metrics. - Cross-reference the two. Do not report them as two separate lists — synthesize:
- Platform pattern: which platform(s) the top performers cluster on, and whether that
matches where most volume (
list_posts) is actually going. A platform getting the most posts but not the top performers is a signal worth naming. - Content theme: read the
contentfield of the top performers for a shared subject, format, or hook — do not invent a theme that isn't visibly there. - Timing/cadence: use
published_at/scheduled_at/created_atto note posting frequency and whether performance clusters around specific days or a specific run of posts. - Status mix: flag if a large share of
list_postsis stuck indraftorfailed— that is itself a finding, not just performance context.
- Platform pattern: which platform(s) the top performers cluster on, and whether that
matches where most volume (
- Produce a short brief with this shape, not a longer one:
- What's working — 2-4 bullets, each citing a specific post or pattern, never a vague generality like "engaging content performs well."
- What to do next — 1-3 concrete, specific suggestions tied directly to the evidence above (e.g. "post more on the platform/format that's already outperforming," not generic social media advice).
- Caveats — anything the data can't support yet (see below).
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.
- 8d ago First seen · 79 lines · 89 tokens per session scan A 766a5ec36b97
content-performance-audit is a skill published in the GitHub repository Mora-AI-Content-Studio/mora-claude-plugin (0 stars, last pushed 18d ago), licensed MIT. It adds 89 tokens to every session and 1,101 once invoked, about $0.0004 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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