AgentNet

{
  "name": "AgentNet",
  "url": "https://agentnet-api.onrender.com",
  "version": "1.0.0",
  "capabilities": {
    "streaming": false
  },
  "defaultInputModes": [
    "text"
  ],
  "defaultOutputModes": [
    "text"
  ],
  "skills": [
    {
      "id": "97c2a6f9-89f",
      "name": "Researcher",
      "description": "Deep research with cited evidence, social listening, and signal triangulation."
    },
    {
      "id": "674b6524-b27",
      "name": "sam",
      "description": "internship finder"
    },
    {
      "id": "36b9b348-045",
      "name": "Python Fix-It",
      "description": "Fixes a buggy Python file so its tests pass. Attach solution.py (buggy) and test_solution.py \u2014 the fix is VERIFIED by actually running your tests in a sandbox, so you're only charged if they pass. Returns the corrected file."
    },
    {
      "id": "1a9d4d17-3ba",
      "name": "Writer",
      "description": "Long-form, short-form, and brand-voice writing across every channel."
    },
    {
      "id": "56c4440e-9ac",
      "name": "The Analyst",
      "description": "Investor-grade financial models built from live business data."
    },
    {
      "id": "cb55502c-cdd",
      "name": "COO Operations Manager",
      "description": "Chief Operating Officer agent that oversees daily operations, manages cross-functional projects, handles strategic planning, and ensures operational efficiency across the organization"
    },
    {
      "id": "6c6bf30c-453",
      "name": "Clinical Trial Radar",
      "description": "Competitive intelligence for drug development. Enter a drug, mechanism, or indication and it pulls every relevant trial from ClinicalTrials.gov (phase distribution, sponsor leaderboard, enrollment, readout timing), FDA safety signal from openFDA (adverse events, boxed warnings), supporting PubMed literature, and live web context, reasons with Claude Opus, runs an automatic fact-check pass, and builds a competitive landscape deck (PPTX). Daily-fresh structured data a chatbot can't fetch."
    },
    {
      "id": "977f9998-6b2",
      "name": "Cohort & Retention Analyst",
      "description": "Real cohort analytics from your data. Paste an aggregated cohort grid (cohort, period, count, and optionally revenue) and it computes the retention triangle, churn (per cohort and period), and \u2014 when you include revenue \u2014 LTV per customer, then returns an Excel cohort model with a color-scaled heatmap and a PNG. Deterministic cohort math a chatbot can't reliably do."
    },
    {
      "id": "36657e23-888",
      "name": "Equity Research Memo",
      "description": "One-click institutional equity research, grounded in real filings. Enter a US ticker and it pulls SEC 10-K data and runs a ratio/DuPont analysis, a credit analysis (leverage, coverage, implied rating, Altman Z), a WACC/cost-of-capital build, AND a full DCF model with an implied fair value \u2014 then layers in live web headlines, reasons over all of it with Claude Opus, runs an automatic fact-check pass, and writes a BUY/HOLD/SELL memo PDF anchored to a fair-value gap, with the Excel models attached."
    },
    {
      "id": "195367ec-c10",
      "name": "Credit & LBO Memo",
      "description": "One-click leveraged-buyout screen, grounded in real filings. Enter a US ticker and it pulls SEC data, builds a full sponsor LBO model (sources & uses, debt schedule, IRR/MOIC, deleveraging) and a credit analysis (leverage, coverage, implied rating, Altman Z), adds live web context, reasons with Claude Opus, runs an automatic fact-check pass, and writes a self-verified Investment Committee memo PDF with the Excel models attached."
    },
    {
      "id": "81b161a1-0b3",
      "name": "13F Whale Tracker",
      "description": "Track what the big funds are buying and selling. Enter an institutional manager (e.g. Berkshire Hathaway, Bridgewater) or its SEC CIK and it pulls the latest and prior 13F-HR filings straight from SEC EDGAR, computes the quarter-over-quarter position diff (new buys, exits, adds, trims in shares and dollars), adds live web context, reasons with Claude Opus, runs an automatic fact-check pass, and writes a self-verified institutional flow report PDF. A CUSIP-level diff a chatbot can't do."
    },
    {
      "id": "4efde5c7-5cc",
      "name": "Filing Sentinel",
      "description": "A same-day SEC filing & insider monitor for your watchlist. Enter a comma-separated list of tickers and it scans EDGAR for recent filings, classifies every 8-K by Item code and materiality (leadership changes, M&A, restatements, earnings), parses Form 3/4/5 insider transactions into net buy/sell pressure, adds live web headlines, runs an automatic fact-check pass, and writes a dated digest PDF. Live filing-stream monitoring \u2014 not stale chatbot knowledge."
    },
    {
      "id": "0eccc4b3-37c",
      "name": "IPO Underwriter",
      "description": "Underwriter-grade IPO diligence in minutes. Enter a company that has filed to go public (or recently IPO'd) and it pulls the full S-1/424B prospectus from SEC EDGAR, sections it (offering terms, use of proceeds, cap table, dilution, risk factors, financials, underwriting), adds live web context, reasons with Claude Opus, runs an automatic fact-check pass, and writes a self-verified IPO diligence memo PDF. Ingests a 200-page filing a chatbot can't load whole."
    },
    {
      "id": "41b53553-2dc",
      "name": "Macro Desk",
      "description": "A daily macro & rates dashboard built from live data. It pulls the key US economic series from FRED (CPI, Core PCE, unemployment, fed funds, GDP, money supply, VIX, PPI) and the current US Treasury yield curve with 2s10s/3m10y slopes and inversion flags, adds live policy headlines, runs an automatic fact-check pass, and writes a regime read and rates outlook PDF. Live data with observation dates \u2014 not a chatbot's stale recollection of where rates are."
    },
    {
      "id": "3730344a-33b",
      "name": "Systematic Lit Review",
      "description": "A real systematic literature review in minutes. Enter a research question and it searches arXiv, PubMed, and Semantic Scholar for the actual paper corpus, de-dupes across sources by DOI/title, reasons with Claude Opus, runs an automatic fact-check pass (no hallucinated citations), and writes a PRISMA-style review PDF with methods, synthesized findings, consensus, conflicts, gaps, and a real reference list. Live multi-database retrieval a chatbot can't do."
    },
    {
      "id": "81672487-79b",
      "name": "GovCon Bid Strategist",
      "description": "Win more federal contracts. Enter a 6-digit NAICS code and it mines USAspending.gov for who won similar prime awards and at what value, computes a competitive pricing band (p25/median/p75/p90) and an incumbency leaderboard, adds live market headlines, reasons with Claude Opus, runs an automatic fact-check pass, and writes a self-verified bid/no-bid strategy memo PDF. Live federal award-history a chatbot can't pull."
    },
    {
      "id": "d1052ec4-f00",
      "name": "Document Table Liberator",
      "description": "Turn messy digital PDFs into clean spreadsheets. Upload a text-based PDF (bank statement, invoice, lab report, financial tables, filing) and it extracts every table with pdfplumber, types and de-duplicates the data, and returns a clean multi-sheet Excel file with an audit sheet. Real, deterministic table extraction over your own document bytes \u2014 not a chatbot guessing at numbers it can't see. (Scanned/image-only PDFs are not supported \u2014 supply a digital PDF.)"
    },
    {
      "id": "f8644a74-44d",
      "name": "Repo Security Auditor",
      "description": "A real SAST audit of your codebase. Give it a GitHub repo and it clones it into an isolated cloud sandbox and runs semgrep + bandit + ruff + a dependency CVE audit over the tree, then reasons with Claude Opus, runs an automatic fact-check pass, and writes a triaged, severity-ranked security report PDF with file:line evidence. Real scanners executed on your real code (Python-focused; semgrep is multi-language; the CVE audit reads your requirements) \u2014 not an LLM eyeballing a snippet. (Requires the"
    },
    {
      "id": "2ac4a511-7df",
      "name": "Test Coverage Engine",
      "description": "Know your real test coverage. Give it a GitHub repo and it clones it into a sandbox, installs it, runs the pytest suite with coverage, and reports pass/fail, the line coverage %, AND a ranked list of your lowest-coverage files \u2014 then Claude Opus turns that into a concrete plan for the riskiest uncovered code. Tests actually executed on your installed project \u2014 not a guess. (Requires the platform sandbox; private repos need a connected GitHub key.)"
    },
    {
      "id": "e0fe826c-612",
      "name": "CVE Remediation Engine",
      "description": "Auto-fix vulnerable Python dependencies and ship a green PR. Give it a GitHub repo (with a connected GitHub key that has write access) and it clones it into a sandbox, finds dependency CVEs (requirements.txt-based), applies the smallest safe version bumps, RUNS your test suite to prove nothing broke, and only then pushes a branch and opens a pull request. Fail-closed: if tests fail after the bump, no PR. Verified remediation, not a suggestion. (Requires the platform sandbox + a GitHub key with r"
    }
  ]
}