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 agentmods add instructions/alessio-web-dev/social-cli-mcp/claude-mdgit clone --depth 1 https://github.com/alessio-web-dev/social-cli-mcpWrote 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/instructions/alessio-web-dev/social-cli-mcp/claude-md)<a href="https://agentmods.dev/instructions/alessio-web-dev/social-cli-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/alessio-web-dev/social-cli-mcp/claude-md.svg" alt="Measured on agentmods" 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 | $0.02758 | $0.02758 |
| Opus 5 | $0.01379 | $0.01379 |
| Sonnet 5 | $0.00552 | $0.00552 |
| Haiku 4.5 | $0.00276 | $0.00276 |
Grade A, and why
social-cli-mcp CLAUDE.md 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 5d 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
v7.0 | flutur-cc | 2026-02-07
GRAFO
S.1 "SurrealDB" :graph @localhost:8000 ns=social db=analytics root/root .schema → src/db/schema.surql .fn → {outreach_status, data_freshness, top_hashtags, daily_analytics, recent_correlations}
S.2 "Supabase" :storage+ai | file storage + Claude Vision labeling .schema → supabase/migrations/001_photos_schema.sql .client → src/db/supabase-client.ts .sync → npx tsx scripts/sync-supabase-photos.ts [import|label|sync|status]
S.3 "Keychain" :credentials service="social-cli-mcp" .api → src/core/credentials.ts | getFromKeychain() setInKeychain() .ok = {Twitter, Instagram, Gmail, Telegram, Anthropic} .setup = {YouTube, Supabase} .missing = {LinkedIn, TikTok}
S.4 "8i8.art" :epk Next.js 14.2→Vercel .config → link-hub/src/lib/artist-config.ts .utm = ?utm_campaign=beach → hero swap .cookies = zero σ₂ send link NOT PDF | PDF only when explicitly requested
ENTITÀ CENTRALI
E.1 "artist_profile:flutur" :nodo-centrale @S.1
→creates→ E.2
→performs_at→ venue
E.2 "software_project:jsom" :exit @github.com/alemusica/jsom
→targets→ {Lovable, Vercel, Prisma, YC}
=$ 6-7 fig
email →sent_to→ venue
content →taken_at_gig→ gig →performed_at→ venue
post →uses_hashtag→ hashtag
post →belongs_to_pillar→ content_pillar
story_fragment →fragment_inspires→ platform_content
story_fragment →fragment_in_arc→ story_arc
web_research →memory_link→ entity (via researchStore.save)
FLUSSI DATI
M.1 instagramFetcher ← IG API (10 calls/wk budget) → S.1:audience_snapshot
M.2 youtubeFetcher ← YT API OAuth2 → S.1:youtube_snapshot
M.3 correlator ← {M.1, M.2, S.1:epk_analytics} → S.1:analytics_correlation
| email→views→visit→reply pattern, 3-day window
M.4 insightsArchiver → M.5 → M.6
M.5 editorialIntelligence | corridor IT↔GR 70%
M.6 contentDrafter :interview | NON inventa, chiede
.styles = {storytelling, minimal, poetic, educational, bridge}
.guard = "Cosa NON devo inventare?"
M.7 email-guard :safety fail-CLOSED
.limit = 25/day
.log → logs/send-log.json (append-only)
→ gmail-sender → S.1:email →sent_to→ venue
M.8 duplicateChecker :auto
| exact + 70% similarity + topic cooldown 7d
.track → {analytics/posted-tweets-index.json, analytics/posted-instagram-index.json}
M.9 storyStore :editorial | biographical narrative fragments
.save → story_fragment → memory_link (entities)
.query → byTheme, forChannel, unpublished, byEntity
M.10 researchStore :cache | web research persistence
σ₂ BEFORE WebSearch → researchStore.find(topic) | skip if <7d
σ₂ AFTER WebSearch → researchStore.save() | ALWAYS
.query → find(topic), search(query), recent()
M.11 gmailReader :inbox | Gmail API scan + Message-ID dedup
.scan → outreach_reply (SCHEMAFULL, UNIQUE gmail_message_id)
.scanSent → email (sent folder scan)
.getThread → full Gmail thread (sent+reply)
.findThreadByMessageId → RFC2822 → gmail_thread_id
.classify → human_reply | auto_reply | bounce
.persist → outreach_reply + memory_link(venue)
M.12 conversationStore :threads | unified sent+reply thread view
.get(venue) → OutreachConversation (chronological messages)
.dashboard() → all conversations, status, action needed
.backfillThreadIds() → link email records to Gmail threads
.syncTracking() → tracking.json → email table
.getGmailThread(venue) → live Gmail API thread
M.13 intelligenceRouter :orchestrator | event→action dispatcher
.route(event) → IntelligenceBriefing {logistics, cluster, conversation, actions}
.routeReply(venue, email, type, preview) → auto-briefing on reply
.formatTelegram(briefing) → Telegram digest with costs + cluster + actions
.formatConsole(briefing) → full console output
| AUTO-TRIGGERS: morning-check runs router on every human reply
| Logistics dept: flight + baggage + accommodation + break-even
| Cluster dept: nearby venues in same country, contactable count
| Conversation dept: thread status, suggested next action
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.
- 5d ago First seen · 226 lines · 2,758 tokens per session scan A 6374fb4e1864
social-cli-mcp CLAUDE.md is an instructions file published in the GitHub repository alessio-web-dev/social-cli-mcp (7 stars, last pushed 5mo ago), licensed MIT. It adds 2,758 tokens to every session, about $0.0138 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.
Other instructions, from other repositories
GPT-RAG release.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.
apex-accelerator vendor-prompting.instructions.md
Vendor prompting best-practice rules for Anthropic Claude and OpenAI GPT-5.6-Terra agents and prompts. Each rule cites a rule ID in the vendor-prompting skill rules.json registry. Validator: npm run lint:vendor-prompting.
ken CLAUDE.md
Claude Code instructions for townsendmerino/ken, covering claude.md, what this is, repository ownership (read this first), commands and embedding parity & golden fixtures (now in aikit).
rag-code-mcp copilot-instructions.md
Instructions for doITmagic/rag-code-mcp, covering copilot instructions - ragcode mcp, ⚖️ the golden rule, project overview, architecture & patterns and developer workflows.
ZipAI CLAUDE.md
Claude Code instructions for nickdesi/ZipAI, covering claude.md — zipai: ultra-dense token optimizer, rules, 1. zero filler, 2. ambiguity and 3. prompt caching.
gpu-ai-skills CLAUDE.md
Claude Code instructions for intel/gpu-ai-skills, covering claude.md, what this repository is, repository structure, commands and validation (required before any skill change).