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.
/plugin marketplace add indranilbanerjee/socialforge/plugin install socialforgeWrote 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/socialforge/ingest-performance)<a href="https://agentmods.dev/skills/indranilbanerjee/socialforge/ingest-performance"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/socialforge/ingest-performance/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/socialforge/ingest-performance"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/socialforge/ingest-performance.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 | $0.00146 | $0.00900 |
| Opus 5 | $0.00073 | $0.00450 |
| Sonnet 5 | $0.00029 | $0.00180 |
| Haiku 4.5 | $0.00015 | $0.00090 |
Grade A, and why
ingest-performance 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 9d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/socialforge:ingest-performance — real numbers into the wins rung
/socialforge:ideate-month compounds "what worked last month." Before this
skill, that meant whatever someone remembered in the planning call — and
memory favors the post that felt good, not the one that performed. This skill
turns the platform's own export into the record ideation reads.
Step 1 — Get the export
Ask the user for the analytics export covering the month. Any CSV works if it
has a column identifying the post (post_id, post, id) that matches the
calendar's post ids, plus whichever metrics the platform provides
(impressions/views, likes/reactions, comments, shares/reposts, saves, clicks,
follows — header aliases are normalized automatically). If the export keys
posts by URL or caption instead of the calendar id, help the user add a
post_id column first — matching is by calendar id, deliberately: wins must
map back to the topics and pillars that produced them.
Step 2 — Ingest
python ${CLAUDE_PLUGIN_ROOT}/scripts/ingest_performance.py --action ingest \
--brand {brand} --month {YYYY-MM} --csv {export.csv} --source "{platform} export"
- Rows matching calendar post ids are stored in
output/{brand}/{month}/performance.json(repeat ingests append — one CSV per platform is normal). - Unmatched rows are listed in the output, never silently dropped. Show the user the unmatched list; a typo'd id is data lost from the wins rung.
- Exit 3 = nothing matched. Stop and reconcile ids before proceeding.
Step 3 — Rank the wins
python ${CLAUDE_PLUGIN_ROOT}/scripts/ingest_performance.py --action wins \
--brand {brand} --month {YYYY-MM}
The ranking is deliberately conservative:
- Sample floor (default 100 impressions): a post nobody saw cannot be a
win, only noise. Below-floor posts are reported as
unrankedwith the reason. - Margin rule (default 1.5× the month's median engagement rate): a "win" must beat the month, not merely top a flat list.
- Unmeasured is not zero: missing impressions →
engagement_rate: null, and the post lands inunranked, not at the bottom of the ranking. - A flat month returns
"status": "no_clear_wins"— report that honestly. Compounding a non-win manufactures a false signal for next month's plan.
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.
- 9d ago First seen · 71 lines · 146 tokens per session scan A 9a01d2dcc07d
ingest-performance is a skill published in the GitHub repository indranilbanerjee/socialforge (37 stars, last pushed 22d ago), licensed MIT. It adds 146 tokens to every session and 900 once invoked, about $0.0007 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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