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 indranilbanerjee/neels-plugins --skill match-assetsgit clone --depth 1 https://github.com/indranilbanerjee/neels-pluginsWrote 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/indranilbanerjee/neels-plugins/match-assets)<a href="https://agentmods.dev/skills/indranilbanerjee/neels-plugins/match-assets"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/neels-plugins/match-assets/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/indranilbanerjee/neels-plugins/match-assets"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/neels-plugins/match-assets.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 | $0.00025 | $0.00983 |
| Opus 5.5 | $0.00010 | $0.00393 |
| Sonnet 5.5 | $0.00005 | $0.00197 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
match-assets scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to match-assets — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/socialforge:match-assets — Asset Matcher
Match brand assets to parsed calendar posts using the multi-factor scoring algorithm. Assigns one of 4 creative modes per post.
Context efficiency
Asset-heavy skill. Grep before Read the asset catalog (${CLAUDE_PLUGIN_DATA}/socialforge/brands/<brand>/asset-index.json) — never list the asset directory. Reference generated images / videos by path, not by loading metadata. Brand profile loads once per session.
Prerequisites
- Calendar parsed (calendar-data.json exists)
- Asset index built (asset-index.json exists)
If either is missing, prompt: "Run /socialforge:parse-calendar first, then /socialforge:index-assets."
The Matching Algorithm
For each post, calculate a multi-factor score against every indexed asset:
| Factor | Weight | What It Measures |
|---|---|---|
| Tag Overlap | 30% | Post keywords vs asset tags |
| Suitability Match | 25% | Asset's "suitable_for" vs post context |
| Content Bucket Match | 20% | Does asset suit this content bucket? |
| Crop Feasibility | 15% | Can asset be cropped to all required platform ratios? |
| Freshness | 10% | Favours assets not already used this month |
Freshness factor: scored as 1 - penalty and weighted at 10% alongside the other four factors (the five weights sum to 1.00). Penalty by prior uses this month: 0 uses = 0.00 | 1 use = 0.15 | 2 uses = 0.40 | 3+ uses = 0.70. Reusing an asset within the same week adds a further 0.50 to the penalty (capped at 1.00).
Creative Mode Assignment
| Score Range | Recommended Mode |
|---|---|
| > 0.8 | ANCHOR_COMPOSE or ENHANCE_EXTEND |
| 0.5 - 0.8 | ENHANCE_EXTEND or STYLE_REFERENCED |
| 0.3 - 0.5 | STYLE_REFERENCED |
| < 0.3 | PURE_CREATIVE |
Also selects 2-5 style reference images per post (always fed to AI generation alongside prompts).
Process
- Load calendar-data.json and asset-index.json
- For each post: extract keywords → score all assets → rank → assign mode
- Select style references per post
- Generate coverage report
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.
- 2d ago First seen · 89 lines · 25 tokens per session scan A 12104e8335c9
match-assets is a skill published in the GitHub repository indranilbanerjee/neels-plugins (6 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 983 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to match-assets, differing in 0 lines, and is treated as a copy.
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