The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Starlog listing page.
Vet a package before your AI coding agent uses it — authoritative facts (CVEs, license, maintenance), free, local, no account.
Vet a package in one command — nothing to install, no API key, no account:
Then wire it into your coding agent (Claude Code, Cursor, Copilot, Codex):
Source-available under BUSL-1.1 — free to use, modify, and self-host; converts to Apache-2.0 in 2030. Details ↓
AI coding agents (Claude Code, Cursor, Copilot) pick libraries from training recall — a snapshot of scraped code, frozen at a cutoff date and ranked by how often an option appeared, not by what fits your task or what's safe now. That recall can't know about a CVE disclosed last week, and it has never seen your company's internal libraries. The agent recommends anyway, with the same confidence either way.
The failure modes are measurable: research finds ~49% of AI-suggested dependencies carry known vulnerabilities and ~34% are hallucinated outright — the package doesn't exist. And for whole categories — most dangerously auth — agents default to hand-rolling custom code instead of reaching for a vetted library.
You can't fix recall by prompting harder. Starlog puts authoritative, dated facts in front of your agent at decision time. Its hero surface is vetting by name — starlog facts <package> returns known CVEs/incidents, SPDX license + risk, and maintenance status (or an honest "no facts on file") — so the install/avoid/pick call rides on facts, not recall. It runs entirely on your machine as an MCP server and a package-install hook, no API key, no sign-up. A companion starlog_search finds candidate packages for a capability; facts vet the pick.
Does it actually change what the agent decides? Yes — measured before/after, on the venue that matters (private libraries and post-cutoff advisories). → the validated result.
starlog_facts MCP tool — your agent looks up authoritative facts about a specific package before recommending it: known CVEs/supply-chain incidents, SPDX license and license risk, maintenance status (active/deprecated/abandoned/compromised), and effect surface. In a 4-model benchmark, agents called this tool unprompted on package decisions (100% recall, 98% specificity) and it moved them toward the correct install/avoid/pick call. Every record is sourced, verified, and dated — each result shows an "as of <date>" line so a stale "no known vulns" is never mistaken for a fresh one. A package with no record returns an honest "no facts on file." Facts are three independent layers, composed at query time: L1 capability/effect-surface (immutable), L2 reputation/vuln/license/maintenance (mutable — carries the as of recency), L3 org policy (your suitability verdict). Override or extend any layer locally: point STARLOG_PRIVATE_FACTS at a JSON file with independent l1/l2 arrays (internal packages, license rulings) and STARLOG_POLICY at an org policy ({ org, rules }) for allow/deny/flag verdicts. With STARLOG_API_KEY set, org-private overlays and policy come from the hosted facts API (local corpus is the offline fallback); starlog facts push uploads your org's overlays + policy. See docs/FACTS-CONTRACT.md.npm install / pnpm add / yarn add / pip install and surfaces that package's facts (known incidents, license, maintenance) before the agent builds on it. Advisory — it informs the next move, it doesn't block the install. Packages with no record are queued for coverage.starlog_search MCP tool — discovery: find candidate packages for a capability (org-sanctioned options first), then vet the named pick with starlog_facts. Discovery surfaces what exists; facts vet it.starlog_advise MCP tool — when your agent sees DIY or repeated capability code, advises MIGRATE to a safe library (e.g. Clerk/Auth0/Supabase over DIY auth) or PACKAGEIZE only when no safe corpus alternative exists. Tracks patterns in .starlog/patterns.json.starlog facts / starlog search / starlog advise / starlog patterns CLI — the same facts, discovery, and migrate-or-packageize advisories from your terminal.STARLOG_API_KEY opts into the hosted facts/search tiers (with local fallback) — get a key at starlog.dev and wire it with starlog init --api-key <key>; anonymous, opt-out usage telemetry is the only thing sent otherwise — see Telemetry.This repo ships the engine plus a curated facts corpus and a discovery corpus of 26 capability manifests across 7 categories (including authentication playbooks for migration).
This wires Starlog into Claude Code (and drops instruction files for Cursor, Copilot, Codex):
~/.claude/settings.json — exposes starlog_facts (vet a package by name), starlog_search (discover candidates), and starlog_advise (migrate-or-packageize for DIY patterns), and wires your per-project private overlays (${CLAUDE_PROJECT_DIR}/.starlog/*) into the agent so internal-package facts + discovery work automatically in each projectPrefer a bare starlog command over typing npx? Install it globally:
If
starlogthen reportscommand not found, your npm global bin directory isn't on yourPATH(a common npm setup gap — not a Starlog issue). Either runexport PATH="$(npm prefix -g)/bin:$PATH"(add it to your shell profile to persist), or just keep usingnpx starloghq init/npx starloghq facts <pkg>, which always work without any PATH setup. If the install itself printed anEACCES/permission error, it didn't complete — fix your npm prefix or usenpx.
Add --project to also drop Starlog guidance into your project's CLAUDE.md; preview without writing, or remove cleanly:
Don't hand-author facts for every internal repo — point Starlog at a directory of checkouts and it derives them in one pass:
For each published package it finds (npm package.json and Python pyproject.toml), it derives:
.starlog/private-facts.json — license + license risk (from the manifest, or detected from the LICENSE file), maintenance from git last-commit recency, stamped source: analyzer with a dated as of. Your agent vets these by name..starlog/private-corpus.json — captures each manifest's description + keywords so your agent can find internal packages by capability via starlog_search, not just vet them by name..starlog/policy.suggested.json — flag candidates (e.g. strong-copyleft, no declared license) derived from the signals. These are proposals the agent does not read — review them, then adopt the ones you trust with starlog facts policy <pkg> flag.Source never leaves your machine; only derived facts are written. Re-run anytime to refresh (it merges over existing facts and regenerates suggestions). Repos with no published name — or no description — are reported, never fabricated. Known-vulnerability scanning and remote GitHub-org enumeration are on the roadmap.
starlog init writes this for you automatically. To configure by hand, add to ~/.claude/settings.json:
This is the same launch command MCP registries use. (From a local source clone instead, point node at dist/mcp.js — $(npm root -g)/starloghq/dist/mcp.js for a global install, or your clone's path.) The server exposes two tools: starlog_facts (an authoritative per-package fact lookup — CVEs, license, maintenance) and starlog_search (a natural-language capability query with optional category, stack, and top_k filters).
Vet a package by name — the hero. Local, no key, no network:
A package with no record returns an honest "No facts on file" — not a guess. Add --format json for machine-readable output with the independent l1 / l2 / l3 layers.
Discover candidates for a capability, then vet the named pick with facts:
Search ranks locally with the keyword ranker — scores are absolute (a strong match lands in the 70s–80s), so a query outside the indexed categories returns "no strong match" rather than a confident wrong answer. Keyless, the candidate set is the bundled corpus (no network). With STARLOG_API_KEY set, candidates come from the hosted full corpus (api.starlog.dev/search) and are ranked by the same local engine — so a key widens what can be found, never how it's scored; any hosted hiccup silently falls back to the bundled corpus.
The model structurally can't know your private @acme/* packages exist — so this is where facts change the most decisions (DIY → the org's sanctioned library). You don't hand-write JSON; two commands author the overlays, and starlog init already wired the agent to read them per-project:
These write .starlog/private-corpus.json (discovery) and .starlog/private-facts.json (vetting) in your project. Because starlog init bakes ${CLAUDE_PROJECT_DIR}/.starlog/* into the MCP server's env, your coding agent picks them up automatically in that project — no shell export, nothing to re-run. Confirm with starlog doctor (it reports the wiring and what each project has authored). For richer overlays — full l1/l2 arrays, org STARLOG_POLICY allow/deny verdicts, or pushing to the hosted API with starlog facts push — see docs/FACTS-CONTRACT.md.
Starlog vets a package as three independent layers, composed at query time — never collapsed into one blurry "score":
| Layer | Answers | Mutability |
|---|---|---|
| L1 capability / effect-surface | what does the code do? | immutable |
| L2 reputation overlay | what's known? — CVEs, license, maintenance | mutable; carries the dated as of recency |
| L3 org policy | is it allowed here? | your rules → allow / deny / flag |
starlog facts <pkg> composes the three for the caller and returns them — or an honest miss — over the MCP server, the CLI, or the install hook. The corpus is local and cacheable; override or extend any layer with STARLOG_PRIVATE_FACTS (internal packages, license rulings) and STARLOG_POLICY. The full contract: docs/FACTS-CONTRACT.md.
Discovery (starlog_search) is a separate surface: it ranks capability manifests against each library's solves / best_for / stack_affinity with a local keyword ranker, reporting an absolute score so an out-of-corpus query returns "no strong match" instead of a forced result. The candidate set is the bundled corpus, or — with STARLOG_API_KEY set — the hosted full corpus, ranked by the same local engine either way. When your agent installs a package with no manifest yet, the hook queues it (.starlog/pending.json) for coverage.
For the full picture — surfaces, engine, data sources, and what telemetry leaves the machine — see docs/ARCHITECTURE.md (with diagrams).
The real test of a facts tool isn't "does it return data" — it's "does the agent decide differently." Measured before/after (control = recall only; treatment = same prompt + Starlog facts):
@acme/* packages; facts are how it learns they exist.posthog-node, facts add "pin away from the malicious 4.18.1 / 5.11.3 / 5.13.3" — advisory MAL-2025-190925, published after the model's training cutoff. It can't know this; the facts can.zod, fastify) don't change, and node-cache (ambiguous, no ground truth) is deliberately not counted as a win — a tool that books every change as a victory is lying to you.Backed by a powered benchmark across four model vendors: correct adopt/avoid decisions moved ~20% → ~78%, with 100% unprompted adoption.
Full before/after, the honest scope, and the experiment we threw out → docs/VALIDATION.md.
Facts corpus — 42 packages. Curated and dated: known supply-chain incidents (xz, event-stream, ua-parser-js, node-ipc, …), notable deprecations, and clean baselines — each with SPDX license + risk, maintenance status, and an as of date. Extend it for your org via STARLOG_PRIVATE_FACTS (internal packages) without touching the public set.
Discovery corpus — 25 capability manifests across 7 categories:
| Category | Examples |
|---|---|
| Authentication | Clerk, Auth0 |
| Real-time | Socket.IO, Ably, Pusher, Supabase Realtime, ws |
| ORM/Database | Prisma, Drizzle, Kysely |
| Background Jobs | BullMQ, Inngest, Bree |
| Resend, SendGrid, Nodemailer | |
| Feature Flags | LaunchDarkly, PostHog, Flagsmith, ConfigCat, DevCycle |
| Caching | ioredis, Upstash Redis, Keyv, Cacheable |
Note: facts and manifest data are point-in-time — sourced and dated, but a decision aid, not ground truth. Verify anything load-bearing; corrections via PR are welcome.
Unit and e2e tests cover schema validation, corpus loading + integrity, facts/format output, the spawned-CLI round-trip, and search ranking. All run without API keys or external binaries.
Starlog collects anonymous, opt-out usage analytics to understand which
commands, tools, and packages are used. It sends: the command/tool run
(init/facts/search/doctor and the starlog_facts/starlog_search MCP
tools), the CLI/Node/OS version, detected agents, coarse result counts, the
public package names you look up, and your search queries / project
context — with emails, secrets/tokens, absolute file paths, and IP addresses
scrubbed before send.
It never sends your org-private package names (those are redacted to a boolean when you use a private overlay), your username/hostname, or any file contents. It's also disabled automatically in CI and test runs.
A notice is printed on first run and re-shown whenever the disclosure changes (so a broadened collection can never happen silently). Through the MCP tools, the server includes the disclosure in its first tool result (which your agent relays to you) and only begins recording from the next call — so MCP analytics are never collected before you've been shown what's collected. Opt out at any time:
Source-available under the Business Source License 1.1 — see LICENSE. Not an OSI open-source license: free to use, modify, and self-host (non-competing use), and it converts to Apache-2.0 on 2030-06-01.