polysearch-ai 1.0.1

Modular, multi-source research pipeline with citation tier classification. Plug-and-play Python package + Claude Code skill.

polysearch

Multi-source research pipeline with citation tier classification and self-verifying output. A pip-installable Python CLI plus a drop-in Claude Code plugin.

polysearch runs one research topic through several web-backed layers in parallel, synthesizes the results into a cited answer, then checks every citation against the page it came from. What you get back is a markdown report where each source carries an authority tier and each claim has been fetched and matched, not just asserted.

The package installs as polysearch-ai; the import name and CLI are both polysearch.

pip install polysearch-ai

It is modular by credential. A user with only a Perplexity key gets sub-question research and a cited report. Add a Firecrawl key and a synthesis model and the pipeline grounds against live pages and verifies citations. Add source connectors and it folds in community signal. Every layer is gated on its own credential: a missing key swaps in a null provider and the run continues with what it has, rather than failing.

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Quickstart

One key, about a minute:

pip install polysearch-ai
echo "PERPLEXITY_API_KEY=your_key_here" > .env
polysearch --topic "What is the current US federal funds rate?" --depth quick

You get a markdown report (and a sibling JSON) in ./reports/, with citations from Perplexity. A quick run costs roughly $0.10 to $0.50.

The same capability as a Claude Code plugin:

/plugin marketplace add milock/polysearch-ai
/plugin install polysearch

Then research from any prompt, or call /polysearch:research directly. See docs/agent-integration.md for the plugin, skill-copy, generic-harness, and Python-API paths.

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How it works

polysearch runs a first pass across up to four research layers in parallel, synthesizes it, verifies it, and then refines it until the answer covers the question or a guard stops the loop.

                       ┌──────────────────────┐
                       │    polysearch CLI    │
                       └──────────┬───────────┘
                                  │
                       ┌──────────┴───────────┐
                       │     Orchestrator     │
                       └──────────┬───────────┘
                                  │
      ┌───────────────┬───────────┼───────────────┬──────────────┐
      ▼               ▼           ▼               ▼              ▼
┌───────────┐  ┌────────────┐ ┌──────────┐  ┌────────────┐ ┌──────────┐
│  Research  │  │    Web     │ │Community │  │   Deep     │ │  Source  │
│  sub-Qs    │  │ grounding  │ │ signal   │  │  research  │ │  tiering │
│(Perplexity)│  │(Firecrawl) │ │(native)  │  │ (opt-in)   │ │(YAML map)│
└─────┬──────┘  └─────┬──────┘ └────┬─────┘  └─────┬──────┘ └────┬─────┘
      └───────────────┴────────────┴──────────────┘              │
                              │                                  │
                     ┌────────┴─────────┐                        │
                     │    Synthesis     │◄───────────────────────┘
                     │ (OpenAI/Claude)  │
                     └────────┬─────────┘
                              │
                     ┌────────┴─────────┐
                     │ Claim extraction │
                     │  + Verification  │   fetch each cited page,
                     │                  │   match quotes & numbers
                     └────────┬─────────┘
                              │
                     ┌────────┴─────────┐
                     │  Recovery pass   │   re-source weak citations
                     └────────┬─────────┘
                              │
                     ┌────────┴─────────┐
                     │ Refinement loop  │──┐  goal not met? emit new
                     └────────┬─────────┘  │  queries, grow the corpus,
                              │◄───────────┘  re-synthesize, re-verify
                     ┌────────┴─────────┐
                     │  Report writer   │
                     │   (md + json)    │
                     └──────────────────┘

The four first-pass research layers:

1. Research (Perplexity). Decomposes the topic into sub-questions and answers each with citation-aware Sonar results.
2. Web grounding (Firecrawl). Searches the live web, scrapes the top hits, and mines structured facts from HIGH-tier pages.
3. Community signal (native). Reddit, Hacker News, Bluesky, GitHub, X, and YouTube adapters, fused and relevance-gated. Classified COMMUNITY tier: sentiment, not proof.
4. Deep research (opt-in). Perplexity sonar-deep-research for high-stakes topics. On automatically at --depth deep, or forced with --deep-research.

Everything downstream is credential-gated and failure-isolated. One layer raising becomes a note in the report; it never sinks the run.

For the full flow, the refinement-loop design, and the verification-status vocabulary, see docs/architecture.md.

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What makes it different

• Refinement loop. After the first pass, a rubric-based evaluator judges coverage against the topic. If the answer falls short, it emits angle-diverse follow-up queries, runs them, verifies the new material, and re-synthesizes. The loop is bounded by an iteration cap, a cost ceiling, and dry-exit guards, so it grows the answer without running away.
• Citations verified even for deep research. Deep-research and Perplexity narrative answers are mined for claims and checked against their sources like everything else. A figure in a deep-research paragraph still has to survive a fetch-and-match.
• Recovery pass. When the first verification comes back weak, polysearch runs scoped re-sourcing queries to find better citations before it gives up on a claim.
• Cross-process rate limiting. A shared on-disk ledger coordinates API rate limits across concurrent runs, so a 429 in one process backs off its siblings instead of hammering the same endpoint.
• Blocked-source exclusion. Hosts on the hard-blocked list (spam, content farms) are dropped before scraping. If one still resolves, it lands in an "Excluded (blocked sources)" section rather than counting as a citation.
• Authority tiers on every source. HIGH / MEDIUM / LOW / COMMUNITY / SME / UNKNOWN, from a bundled domain map you can override. The report weights sources so you do not treat a forum post like a government filing.

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Install tiers

Each key turns on another layer. A run uses whatever is present and skips the rest. Start with one key and grow. These tiers match resolve_install_tier and .env.example; examples/tiers.md walks through each.

Tier	What you add	What you get	Cost per query
0	PERPLEXITY_API_KEY	Decomposed sub-question research, returned as a cited report	~$0.10–$0.50
1	Firecrawl key + a synthesis model (OPENAI_API_KEY or ANTHROPIC_API_KEY)	Web grounding, cross-source synthesis, and citation verification	~$0.50–$2.00
2	One or more source connectors (SCRAPECREATORS_API_KEY, YOUTUBE_API_KEY, GITHUB_TOKEN, REDDIT_CLIENT_ID/_SECRET)	Higher community coverage and rate limits, plus X and YouTube	Tier 1 + each connector's own cost

The community layer's keyless sources (Reddit, Hacker News, Bluesky, GitHub) run at any tier without a key; connectors raise their rate limits and add the key-gated sources. The X adapter needs SCRAPECREATORS_API_KEY plus a watch list of handles set via POLYSEARCH_X_HANDLES (that is configuration, not a credential). Run polysearch --diagnose to see which layers are active for your current keys.

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CLI reference

polysearch --topic "..." [options]

Flag	Default	Notes
--topic	required	Research subject (also required by --classify)
--depth	standard	quick / standard / deep
--output-dir	./reports/	Where the markdown + JSON are written
--providers	all	Comma-list of first-pass layers to run: research,grounding,community,deep_research,linkedin
--synthesizer	auto	Force openai or anthropic (default: auto by available key)
--verify-budget	per depth	Override the first-pass verification budget, in USD
--no-verify	off	Skip citation verification
--no-recovery	off	Skip the recovery pass after weak verification
--max-iterations	per depth	Override the refinement iteration cap (0 disables the loop)
--deep-research	off	Force the deep-research layer at any depth (needs a Perplexity key)
--classify	off	Print the classifier verdict as JSON and exit (no network)
--diagnose	off	Print credential / tier / layer / output-dir status and exit (no network)
--synthesize-parallel GLOB	—	Cross-synthesize existing report files matching GLOB into one rollup

Synthesizer auto-resolution: if both OPENAI_API_KEY and ANTHROPIC_API_KEY are set, OpenAI is used (cheaper). If only one is set, that one is used. If neither, synthesis is skipped and the report carries the raw layer outputs with a note.

---

Cost by depth

Rough per-query cost. Actual spend depends on how much verification scrapes; cap it with --verify-budget.

Tier	Quick	Standard	Deep
0 (Perplexity only)	~$0.10	~$0.30	~$1.00
1 (+Firecrawl, synthesis)	~$0.30	~$0.80	~$2.50
2 (+community connectors)	~$0.40	~$1.10	~$3.50

The deep-research layer is the largest single cost. It bills on input, output, citation, and reasoning tokens plus search queries, so a deep run costs several times a standard one. Leave it off for routine work.

---

Python API

The one public entry point is run_research, an async coroutine that returns a structured report and (by default) writes the markdown and JSON.

import asyncio
from polysearch import run_research

async def main():
    report = await run_research(
        "What is the current US federal funds rate?",
        depth="quick",
    )
    print(report.synthesis_md)
    print(f"cost: ${report.totals.get('cost_usd', 0.0):.4f}")

asyncio.run(main())

Every layer sits behind a Protocol, so you can inject a bundle of mock or null providers to run fully offline. See docs/providers.md for the protocols and how to add your own, and docs/agent-integration.md for the full keyword-argument list.

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What's in the box

Path	What it is
src/polysearch/	The Python package: provider protocols, orchestrator, CLI.
src/polysearch/providers/	Concrete providers behind each protocol (Perplexity, Firecrawl, OpenAI/Anthropic, deep research, LinkedIn).
src/polysearch/community/	Native community adapters, fusion, and the relevance gate.
src/polysearch/data/	Bundled domain_tiers.yaml and authoritative-source schemas, shipped inside the wheel. Override with POLYSEARCH_DOMAIN_TIERS / POLYSEARCH_SCHEMA_DIR.
skills/research/	The Claude Code skill.
agents/	A thin research-agent template.
examples/	Quickstart script, tier walkthrough, sample output.
tests/	Unit, integration (mocked providers), and opt-in live tests.
docs/	Architecture, providers, configuration, and agent integration.
install.sh	One-line installer for the Claude Code skill.

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A note on LinkedIn and X

The LinkedIn enricher and the X adapter reach those platforms through ScrapeCreators. Automated collection can run against LinkedIn's and X's Terms of Service. Both layers are opt-in and off unless you set SCRAPECREATORS_API_KEY (and, for X, POLYSEARCH_X_HANDLES). You are responsible for using them within the platforms' terms and applicable law.

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Documentation

• docs/architecture.md: the layer flow, the refinement loop, and verification statuses.
• docs/providers.md: the provider protocols and how to add a provider or a community adapter.
• docs/configuration.md: every setting and environment variable.
• docs/agent-integration.md: wiring polysearch into Claude Code or any agent harness.

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Contributing

The provider protocols in src/polysearch/providers/base.py are the easiest place to contribute a new implementation. See CONTRIBUTING.md.

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License and credits

MIT, see LICENSE. polysearch composes several upstream services and one adapted open-source library; full credits are in ATTRIBUTION.md.