Tushare Data
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable…
Install Comps
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence comps --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .claude/skills/comps && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .claude/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/compsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence comps --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .agents/skills/comps && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .agents/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence comps --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .cursor/skills/comps && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .cursor/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/agentii-ai/agentii-investment-intelligence.git --path plugins/vertical-plugins/models-and-pitches/skills/agentii/comps--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence comps --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .gemini/skills/comps && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .gemini/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install agentii-ai/agentii-investment-intelligence compsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .github/skills/comps && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .github/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence comps --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps .opencode/skills/comps && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "comps" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/comps into .opencode/skills/comps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comps", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
comps- GitHub stars
- 207
- Token cost
- ~2.3k tokens
- SKILL.md length
- 775 words
- Files
- 9 (incl. references)
- Skills in repo
- 79
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable…
- Works in 5 steps: Inputs: resolved ticker + peers via… → Build: write a self-contained Python… → Validate: run LibreOffice recalc; audit… → …
- Tasks that involve Trading and backtesting
- SKILL.md covers Preflight, Triggers, Defaults and Methodology, plus 8 more sections
- Reaches agentii.ai
What it does
Comps is an agent skill from agentii-ai/agentii-investment-intelligence. Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable analysis
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/formula-sheet.md`, `references/institutional-defaults.md` and `references/methodology.md`).
It sits in Business, Finance & HR, covering Trading and backtesting and Legal research. The repository describes itself as: Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Trading and backtesting
- Tasks that involve Legal research
Example prompts
- “/comps”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Inputs: resolved ticker + peers via search_companies + search_xbrl_facts for all tickers (revenue, EBITDA, EPS, multiples) +…
- Build: write a self-contained Python script using openpyxl that creates the comps workbook (peer profiles, trading multiples, valuation…
- Validate: run LibreOffice recalc; audit per ## Validation Gates.
- Output: write the artifact path per ## Output File.
- Next: append to agentii.md; hand off to a downstream pitch/review skill if requested.
What it can do on your machine
Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
agentii.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Comps loads about 2.3k tokens when it runs, and up to ~8.1k if it reads all its reference files. Until then it costs about 53 tokens; SKILL.md has 775 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 775 words, ~2,257 tokens.
Download SKILL.mdSave it as
.claude/skills/comps/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- comps
- description
- Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable analysis
- multi_ticker_semantics
- target_with_required_peers
- essentials_modes
- retrieval-scope
- temporal_scope.default_quarters
- 4
- temporal_scope.max_quarters
- 12
- temporal_scope.description
- Typical lookback: 4 quarters, max: 12
- retrieval_scope
- unstructured_document_search
- min_tool_diversity
- 5
Preflight
Run canonical pre-flight per contracts/preflight.md.
Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).
Triggers
- analyze comps analysis
- run comps analysis analysis
- produce comps analysis report
- comps analysis breakdown
- comps analysis deep dive
- build a comps analysis
- assess comps analysis
- quantify comps analysis
- compare comps analysis across peers
- review comps analysis for
- generate comps analysis on
- comps analysis for investment decision
Defaults
| Parameter | Default | Notes |
|---|---|---|
| lookback_years | 3 | Historical data window |
| include_peers | false | Whether to surface a peer comparison block |
Methodology
Retrieval Scope
This skill performs unstructured document search at scale across SEC filings and earnings call transcripts (10-K, 10-Q, 8-K). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
Retrieval Strategy
See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.
Temporal Scope
Default: 12 fiscal quarters (max 20). Financial modeling: trailing 12 quarters (3 fiscal years) for long-range projection inputs.
Tool Allowlist
See frontmatter allowed_tools.
Protocol
Step-by-step execution detail is in references/methodology.md.
Deliverable Chain
Inputs → Build → Validate → Output → Next
- Inputs: resolved ticker + peers via
search_companies+search_xbrl_factsfor all tickers (revenue, EBITDA, EPS, multiples) +get_company_financials. - Build: write a self-contained Python script using
openpyxlthat creates the comps workbook (peer profiles, trading multiples, valuation summary) per## Output Structure. Execute viaBash: python3 script.py. Verify the.xlsxexists. Ifimport openpyxlfails, fall back to.mdsummary withdata_availability: degraded(seecontracts/office-tooling.md). - Validate: run LibreOffice recalc; audit per
## Validation Gates. - Output: write the artifact path per
## Output File. - Next: append to
agentii.md; hand off to a downstream pitch/review skill if requested.
Validation Gates
peer count: between 4 and 8. If failed: If < 4: flag in Coverage Gaps, proceed with available peers. If > 8: trim to top 8 by sector proximity.
trading multiples: include EV/EBITDA + P/E at minimum. If failed: If either missing: flag which multiple is unavailable and why.
comps statistics table: present with mean, median, high, low for each multiple. If failed: If statistics table missing: refuse delivery.
tool diversity: distinct MCP tools used in this invocation >=
min_tool_diversity(5). If failed: flag as depth-insufficient in Coverage Gaps, listing which tool categories were unused (structured data / document retrieval / company metadata / earnings calendar / coverage). This gate does NOT block analysis completion — it is a quality signal for your review.
Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.
Output File
Write the final deliverable to _cross/{descriptive-slug}_{YYYY-MM-DD_HHMM}_comps_{affix}.md or _sector/{sector_name}/{YYYY-MM-DD_HHMM}_comps_{affix}.md .
Show full SKILL.md (345 more words)Show less
Output Structure
The deliverable is a structured markdown report written to the path in ## Output File. Full section-by-section template (headings, tables, and field definitions) lives in references/output-structure.md. Required elements:
- Executive Summary — headline conclusions (≤200 words).
- Core analysis sections — per this skill's methodology and analyst modes.
- Data classification — tag findings
[FACT]/[DEDUCTED]/[VIEW]percontracts/snapshot-synthesis.md. - Coverage Gaps & Citations — inline
/v/citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index. - Output frontmatter — emit the FR-090 structured block per
contracts/output-frontmatter-schema.md.
Citations & memory: follow contracts/citation-and-memory.md — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link; a bottom Citations section provides a non-duplicative roll-up index; the closing TUI reply includes a compact Key Citations list (headline 5–10 facts) of clickable /v/ URLs; and append the run to agentii.md per contracts/agentii-md-schema.md.
Memory & Snapshot
- Memory load (pre-flight): load prior workspace context for the ticker before retrieval — see
contracts/memory-load.md. - Structured output frontmatter: emit the FR-090 block (
key_metrics,conclusions,facts_count,deducted_count,views_count,citation_count) percontracts/output-frontmatter-schema.md. - Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as
[FACT]/[DEDUCTED]/[VIEW]— seecontracts/snapshot-synthesis.md. - Session archival: record the run under
sessions/{YYYY-MM-DD}/and updatesessions/INDEX.mdpercontracts/session-format.md.
Final Summary (TUI)
End the closing chat reply with a compact Key Citations list (headline 5–10 facts), each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link, so the user can cmd+click straight to the exact SEC page. See contracts/citation-and-memory.md.
Error Handling
| Failure Mode | Detection | Action | User-Facing Message |
|---|---|---|---|
| Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." |
| Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." |
| Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." |
| Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." |
| MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |
© agentii-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 8 other files (references) in plugins/vertical-plugins/models-and-pitches/skills/agentii/comps of agentii-ai/agentii-investment-intelligence.
- SKILL.md
- references/formula-sheet.md
- references/institutional-defaults.md
- references/methodology.md
- references/modes.md
- references/output-structure.md
- references/tool-fallbacks.md
- references/validation-checklist.md
- references/wsp-methodology.md
Open the folder on GitHubat commit 86980e1
Compare with similar skills
Comps next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Comps this skillagentii-ai/agentii-investment-intelligence | 207 | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Tushare Datazillionare/zillionare | 319 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 870 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Fintoolsecond-state/fintool | 316 | 1 repos | ~5.9k | Automated safety check: Pass | None | |
| Polyclawchainstacklabs/polyclaw | 360 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 |
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Questions about Comps
What does Comps do?
Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable…. Comps is an agent skill from agentii-ai/agentii-investment-intelligence.
When should I use Comps?
Comps fits situations like: tasks that involve Trading and backtesting; tasks that involve Legal research.
How do I install Comps in Claude Code?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/comps in agentii-ai/agentii-investment-intelligence) into .claude/skills/comps in your project. Claude Code loads it when a task matches its description.
How do I install Comps in Codex?
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a codex`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/comps in agentii-ai/agentii-investment-intelligence) into .agents/skills/comps in your project. Codex loads it when a task matches its description.
Can I use Comps in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentii-ai/agentii-investment-intelligence --skill comps -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/comps, .gemini/skills/comps, .github/skills/comps and .opencode/skills/comps in your project.
What does Comps need to run?
SKILL.md names no scripts, command-line tools or credentials: Comps is instructions for the agent only. Our summary lists: Python 3.
Does Comps access the network?
SKILL.md names 1 domain. In commands or code: agentii.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Comps safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Comps use?
Comps is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Comps use?
About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.8k tokens, read only when the agent opens those files.
What are the alternatives to Comps?
Skills that share tags, products or a category with Comps: Tushare Data (zillionare/zillionare, 319 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 870 stars) and Fintool (second-state/fintool, 316 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Comps?
agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.
Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.