sift

Turn noisy command output into a short, actionable first pass for your coding agent

Local heuristics first. Group repeated failures into likely root causes and next steps before your agent reads the full log.

Get Started

npm install -g @bilalimamoglu/sift

_{Best today on noisy pytest, vitest, jest, tsc, ESLint, common build failures, npm audit, and terraform plan output.}

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Why Sift?

When an agent hits noisy output, it can eventually make sense of the log wall, but it wastes time and tokens getting there.

sift narrows that output locally first. It groups repeated failures, surfaces likely root causes, and points to the next useful step so your agent starts from signal instead of raw noise.

It is not a generic repo summarizer, not a shell telemetry product, and not a benchmark dashboard. It is a local-first triage layer for noisy command output in coding-agent workflows.

Turn 13,000 lines of test output into 2 root causes.

With sift, the same run becomes:

- Tests did not pass.
- 3 tests failed. 125 errors occurred.
- Shared blocker: 125 errors share the same root cause - a missing test environment variable.
  Anchor: tests/conftest.py
  Fix: Set the required env var before rerunning DB-isolated tests.
- Contract drift: 3 snapshot tests are out of sync with the current API or model state.
  Anchor: tests/contracts/test_feature_manifest_freeze.py
  Fix: Regenerate the snapshots if the changes are intentional.
- Decision: stop and act.

In one large test-status benchmark fixture, sift compressed 198,026 raw output tokens to 129. That is scoped proof for a noisy test-debugging case, not a promise that every preset behaves the same way.

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Quick Start

1. Install

npm install -g @bilalimamoglu/sift

Requires Node.js 20+.

2. Try the main workflow

If you are new, start here and ignore hook beta and native surfaces for now:

sift exec --preset test-status -- pytest -q

Other common entry points:

sift exec --preset test-status -- npx vitest run
sift exec --preset test-status -- npx jest
sift exec "what changed?" -- git diff

3. Zoom only if needed

Think of the workflow like this:

• standard = map
• focused = zoom
• raw traceback = last resort

sift rerun
sift rerun --remaining --detail focused

If standard already gives you the likely root cause, anchor, and fix, stop there and act.

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Benchmark Results

The output reduction above measures a single command's raw output. The table below measures one replayed end-to-end debug loop: how many tokens, tool calls, and seconds the agent spent to reach the same outcome in that benchmarked scenario.

Real debug loop on a 640-test Python backend with 124 repeated setup errors, 3 contract failures, and 511 passing tests:

Metric	Without sift	With sift	Reduction
Tokens	52,944	20,049	62% fewer
Tool calls	40.8	12	71% fewer
Wall-clock time	244s	85s	65% faster
Commands	15.5	6	61% fewer
Outcome	Same	Same	Same outcome

Same outcome, less agent thrash.

Methodology and caveats: BENCHMARK_NOTES.md

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How It Works

sift keeps the explanation simple:

1. Capture output. Run the noisy command or accept already-existing piped output.
2. Run local heuristics. Detect known failure shapes first so common cases stay cheap and deterministic.
3. Return a useful first pass. When heuristics are confident, sift gives the agent grouped failures, likely root causes, and the next step.
4. Fall back only when needed. If heuristics are not enough, sift uses a cheaper model instead of spending your main agent budget.

Your agent spends tokens fixing, not reading.

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Key Features

### Test Failure Guidance Collapse repeated pytest, vitest, and jest failures into grouped issues with likely root causes, anchors, and fix hints.	### Typecheck and Lint Guidance Group noisy `tsc` and ESLint output into the few issues that actually matter instead of dumping the whole log back into the model.	### Build Failure Extraction Pull out the first concrete error from webpack, esbuild/Vite, Cargo, Go, GCC/Clang, and similar build output.
### Audit and Infra Risk Surface high-impact `npm audit` findings and destructive `terraform plan` signals without making the agent read everything.	### Heuristic-First by Default Every built-in preset tries local parsing first. When the heuristic handles the output, no provider call is needed.	### Agent and Automation Friendly Use `sift` in Codex, Claude, CI, hooks, or shell scripts when you want downstream tooling to receive a short first pass instead of the raw log wall.

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Presets

Preset	What it does	Needs provider?
test-status	Groups pytest, vitest, and jest failures into root-cause buckets with anchors and fix suggestions.	No
typecheck-summary	Parses tsc output and groups issues by error code.	No
lint-failures	Parses ESLint output and groups failures by rule.	No
build-failure	Extracts the first concrete build error from common toolchains.	Fallback only
contract-drift	Detects explicit snapshot, golden, OpenAPI, manifest, or generated-artifact drift without broadening into generic repo analysis.	Fallback only
audit-critical	Pulls high and critical npm audit findings.	No
infra-risk	Detects destructive signals in terraform plan.	No
diff-summary	Summarizes change sets and likely risks in diff output.	Yes
log-errors	Extracts the strongest error signals from noisy logs.	Fallback only

When output already exists in a pipeline, use pipe mode instead of exec:

pytest -q 2>&1 | sift preset test-status
npm audit 2>&1 | sift preset audit-critical

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Setup and Agent Integration

If you want deeper integration after the first successful sift exec run, start with:

sift install

Most built-in presets run entirely on local heuristics with no API key required. If you want deeper fallback for ambiguous cases, sift also supports OpenAI-compatible and OpenRouter-compatible endpoints.

During install, pick the mode that matches reality: - agent-escalation: sift gives the first answer, then your agent keeps going - provider-assisted: sift itself can ask a cheap fallback model when needed - local-only: keep everything local

Runtime-native files are small guidance surfaces, not a second execution system: - Codex: managed AGENTS.md block plus a generated SKILL.md - Claude: managed CLAUDE.md block plus a generated .claude/commands/sift/ command pack - Cursor: optional .cursor/skills/sift/SKILL.md path when you want an explicit native Cursor skill

Default rule: - use sift exec for the normal first pass - use sift hook only as an optional beta shortcut for a tiny known-command set

Optional local evidence surfaces:

sift gain
sift discover

• gain shows local, metadata-only first-pass history
• discover stays quiet unless your own local history is strong enough to justify a concrete suggestion

If you want the full install, ownership, and touched-files details, see docs/cli-reference.md. The short version: sift does not write shell rc files, PATH entries, git hooks, or arbitrary repo files during install.

If you want this repo's tracked pre-push verification hook to actually run on your machine, you still need to activate it once:

npm run setup:hooks

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Test Debugging Workflow

For noisy test failures, start with the test-status preset and let standard be the default stop point.

sift exec --preset test-status -- <test command>
sift rerun
sift rerun --remaining --detail focused
sift rerun --remaining --detail verbose --show-raw

Useful rules of thumb:

• If standard ends with Decision: stop and act, go read source and fix the issue.
• Use sift rerun after a change to refresh the same test command at standard.
• Use sift rerun --remaining to zoom into what still fails after the first pass.
• Treat raw traceback as the last resort, not the starting point.

For machine branching or automation, test-status also supports diagnose JSON:

sift exec --preset test-status --goal diagnose --format json -- pytest -q
sift rerun --goal diagnose --format json

Diagnose JSON is summary-first on purpose. If read_targets.anchor_kind=traceback and read_targets.context_hint.kind=exact_window, read that narrow range first. If the read target is lower-confidence or search_only, treat it as a representative hint rather than exact root-cause proof.

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Limitations

• sift adds the most value when output is long, repetitive, and shaped by a small number of root causes. For short, obvious failures it may not save much.
• The deepest local heuristic coverage is in test debugging (pytest, vitest, jest). Other presets have solid heuristics but less depth.
• sift does not help with interactive or TUI-based commands.
• sift is not a generic repo summarizer or broad mismatch detector. It works best when the command output itself carries strong failure or drift evidence.
• When heuristics cannot explain the output confidently, sift either falls back to a provider or returns the strongest local first pass it can, depending on how you choose to use it.

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Docs

• CLI reference: docs/cli-reference.md
• Worked examples: docs/examples
• Benchmark methodology: BENCHMARK_NOTES.md
• Contributing and development notes: CONTRIBUTING.md
• Release notes: release-notes

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License

MIT

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Local-first output guidance for coding agents.

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