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snip pivot plan — "The snippet manager for AI agents"

One-liner: Your AI agent shouldn't guess your production commands. snip gives Claude Code, Cursor, and any MCP client a verified, safety-checked command library — versioned in your repo.

Why pivot: the human-memory snippet-manager category is dying (AI assistants answer "what was that docker command" for free). The valuable inversion: AI agents hallucinate commands; snip is the verified, executable, policy-guarded library they pull from. The parts already exist (lib/mcp-server.js, lib/safety.js, lib/team.js with git-checked-in .snip/snippets.json); this plan is composition + repositioning, not a rebuild.

Phase 1 — Reposition (week 1, no new features)

  • Rewrite README top fold: lead with MCP demo (agent transcript: snip_search → snip_exec dry-run → blocked dangerous command). Human CLI/TUI becomes section 2. Comparison table removed.
  • snip mcp install [claude|cursor|goose|continue] — writes the MCP config entry (claude via claude mcp add, cursor via ~/.cursor/mcp.json, goose/continue print config).
  • Slim the install: removed openai (was entirely unused — lib/ai/openai.js uses native fetch); MCP SDK stays as a regular dep (it IS the product) and was already lazy-loaded. Lazy-loaded lib/commands/ui.js in cli.js (blessed + cli-highlight): snip --help 1.1s → 0.11s.
  • Repo cleanup: deleted isolate-*.log, temp-sqljs.db, snip-0.1.0.tgz, root coverage/ (gitignore already covered them). Fixed accumulating signal handlers in lib/storage.js/lib/exec.js with process-level guards.
  • npm metadata: added keywords mcp, model-context-protocol, ai-agents, claude, cursor, mcp-server; agent-first description; bumped to 0.4.0.

Exit criteria: a stranger landing on the README understands "this is for my AI agent" in 10 seconds and is running it in 2 minutes.

Phase 2 — Sharpen the safety story (weeks 2–3)

  • .snip/policy.json (checked into repo): allow/deny patterns, execRequiresApproval, max runtime, allowed languages. Enforced by MCP snip_exec. Turns safety from a hardcoded list into team-governed guardrails.
  • Audit log: every MCP tool call appends to ~/.local/share/snip/audit.jsonl (who/what/when/dry-run/blocked).
  • Approval flow: policy-gated snip_exec returns pending-approval; human confirms via snip approve <id>.
  • Document safety.js regexes as "built-in deny rules" under the policy umbrella.

Phase 3 — Team = the moat (weeks 3–5)

  • Mental model: .snip/ in a repo = "runbook". snip init scaffolds snippets.json + policy.json + README stub. Pitch: code-reviewed commands — agent PRs a snippet, human approves, every teammate's agent can use it.
  • MCP reads team snippets first when cwd is in a repo; tag results source: team|personal.
  • Snippet provenance in MCP responses: author, updatedAt, usage count.
  • Defer hosted sync — git IS the sync backend; "no server, data stays in your repo" is a selling point.

Phase 4 — Launch (week 6)

  • 60-second VHS demo: agent asks for deploy command → gets team's verified one → rm -rf variant blocked by policy → audit log shown.
  • Submit to: Anthropic MCP registry, mcp.so, PulseMCP, Cursor directory, Smithery.
  • Show HN: "snip – a verified command library for AI agents (MCP)".
  • Blog post: "Your AI agent shouldn't guess your production commands"; cross-post r/ClaudeAI, X, dev.to.
  • Per-client setup recipes (Claude Code, Cursor, Goose, Continue).

Cut list (Phase 1)

Freeze (keep code, stop advertising/maintaining): streaks, dashboard, widget, watch-history, discover, stats beyond usage counts. Drop OpenAI generation from the headline — "another AI code generator" muddies "the safety layer for agent commands."

Money / job payoff

  • Job: after Phase 2, the artifact is "policy-enforced, audited command execution for AI agents" — case study + repo = strong interview package.
  • Money (later, optional): free for individuals + git teams; paid tier = org policy management + centralized audit (compliance buyers).