Crawler Summary

stock-qualitative-analysis answer-first brief

Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. --- name: stock-qualitative-analysis description: Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. compatibility: Requires Pyt Capability contract not published. No trust telemetry is available yet. 22 GitHub stars reported by the source. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

Best For

stock-qualitative-analysis is best for general automation workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 100/100

stock-qualitative-analysis

Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. --- name: stock-qualitative-analysis description: Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. compatibility: Requires Pyt

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals22 GitHub stars

Capability contract not published. No trust telemetry is available yet. 22 GitHub stars reported by the source. Last updated 4/15/2026.

22 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Fakehank

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 22 GitHub stars reported by the source. Last updated 4/15/2026.

Setup snapshot

git clone https://github.com/FakeHank/stock_qualitative_analysis_skills.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Fakehank

profilemedium
Observed Apr 15, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 15, 2026Source linkProvenance
Adoption (1)

Adoption signal

22 GitHub stars

profilemedium
Observed Apr 15, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

0

Snippets

0

Languages

typescript

Parameters

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. --- name: stock-qualitative-analysis description: Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. compatibility: Requires Pyt

Full README

name: stock-qualitative-analysis description: Create comprehensive and deeply analyzed buy-side style qualitative stock analysis reports from filings and public sources with strict citations, chapter-by-chapter workflow, and placeholders for missing evidence. Emphasizes active extraction and detailed analysis of SEC information. Use for Chinese qualitative analysis of listed companies. compatibility: Requires Python 3. Network access needed for SEC EDGAR fetches. metadata: author: sysyphus version: "0.1"

Stock Qualitative Analysis Skill

When to use

Use this skill when a user asks for a qualitative stock analysis report (定性分析) that must be evidence-based and formatted as a structured report. This skill emphasizes strict citations and non-hallucination behavior.

Inputs

  • Company name (required)
  • Ticker / exchange (optional but recommended)
  • Market context (US / HK / CN / other)
  • Time window (e.g., FY2015–FY2024; latest quarterly)
  • Language preference (Chinese default; English if requested)
  • Sources:
    • User-provided filings (PDF or HTML)
    • SEC EDGAR fetch (optional, if allowed)
    • Other public sources (only if cited)

Outputs

  • A Markdown report following the template structure in assets/report-template.md
  • Each section contains: 结论要点 / 详细情况 / 证据与出处 (or English equivalents when English output is requested)
  • Final 来源清单 with SEC filings and other sources in reverse-chronological order

Core rules (non-negotiable)

  • Do not state facts without a source.
  • Any factual claim MUST include a source string; otherwise use a placeholder in 【...】 describing what is needed.
  • Actively analyze sources: Go beyond surface-level summaries. Extract specific details, quantitative data, and contextual insights relevant to each section of the report template.
  • Comprehensive filling: Make the best effort to fill all sections of the report template. If information is truly missing from the provided sources, use a specific placeholder indicating what is missing.
  • If real-time data is required, explicitly state that the user must verify freshness.
  • No investment advice, price targets, or trading recommendations.
  • Default output language: Chinese. If the user query is in English, respond in English.

Execution

  • Intake: confirm company name, ticker/exchange, market, time window, and allowed data sources.
  • Pre-check local data: before any remote fetching, verify whether local filings are sufficient; only fetch remotely if local data is insufficient.
  • Acquire sources: use scripts/build_source_manifest.py to pull SEC filings and ingest local PDFs.
  • Extract key 10-K sections (HTML): use scripts/extract_sec_html_sections.py to produce per-item text files (e.g., Item 1/1A/7/8) before analysis.
  • Section-by-section generation (Agent-driven): for each section in assets/report-template.md, the Agent expands the section in sequence, producing 结论要点 / 详细情况 / 证据与出处 based on the available sources and citing evidence.
  • Progressive write-back: before starting summaries, determine whether a local report file exists; after completing each section, write the content into that file.
  • Finalization: rewrite 投资要点概览 after all sections are complete, then update 来源清单.

Usage

  • The Agent executes the section loop at runtime based on the template headings.
  • The Agent MUST attempt to fill every section using provided sources and mark missing facts with explicit placeholders.
  • If the user asks for English output, the Agent translates the template headings and section labels consistently (e.g., Conclusion / Details / Evidence) while preserving the report structure.

Data acquisition

  • SEC EDGAR fetch: scripts/fetch_sec_edgar.py
  • Local PDF ingestion: scripts/ingest_local_pdfs.py
  • Source manifest: scripts/build_source_manifest.py
  • HTML section extractor: scripts/extract_sec_html_sections.py

Citation format

  • SEC filings: Form 10-K/10-Q/20-F/6-K + 年度/日期 + 章节/标题
  • Web sources: 机构/网站 + 发布日期 + 标题

Examples

Example request

“参考 SEC filings,帮我做 AAPL 的定性分析,按模板输出。”

Example output shape

Use assets/report-template.md and fill each section with facts + citations. Unknowns become placeholders.

References

  • Guardrails and writing style: references/prompt-guardrails.md
  • Report template: assets/report-template.md
  • Validation checklist: references/validation-checklist.md
  • Goldenset examples: references/goldenset.md

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/snapshot"
curl -s "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/contract"
curl -s "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T02:46:32.471Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Fakehank",
    "href": "https://github.com/FakeHank/stock_qualitative_analysis_skills",
    "sourceUrl": "https://github.com/FakeHank/stock_qualitative_analysis_skills",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T03:18:28.342Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T03:18:28.342Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "22 GitHub stars",
    "href": "https://github.com/FakeHank/stock_qualitative_analysis_skills",
    "sourceUrl": "https://github.com/FakeHank/stock_qualitative_analysis_skills",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T03:18:28.342Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/fakehank-stock-qualitative-analysis-skills/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to stock-qualitative-analysis and adjacent AI workflows.