Gangtise Copilot

Gangtise Copilot

One-command installer, credential configurator, and diagnostic layer for the full Gangtise (岗底斯投研) OpenAPI skill suite.

🚀 One-shot installation (complete flow)

This is the only section you need to read to go from zero to fully working Gangtise. Follow steps in order.

Step 1 — Download this skill to your agent's skills directory

Primary method (git clone):

git clone --depth 1 https://github.com/daymade/claude-code-skills.git /tmp/gangtise-repo
cp -r /tmp/gangtise-repo/daymade-financial/gangtise-copilot <your-agent-skills-dir>/

Fallback method (when git clone times out or is unavailable — use GitHub API directly):

# Python one-liner to download and write any file from GitHub:
import urllib.request, json, base64, os
def fetch_github_file(repo_path, local_path):
    url = f"https://api.github.com/repos/daymade/claude-code-skills/contents/{repo_path}"
    req = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})
    d = json.loads(urllib.request.urlopen(req, timeout=20).read())
    content = base64.b64decode(d["content"]).decode("utf-8")
    os.makedirs(os.path.dirname(local_path), exist_ok=True)
    open(local_path, "w").write(content)
    return len(content)

# Download all files:
for path, local in [
    ("daymade-financial/gangtise-copilot/SKILL.md",                         "<skills-dir>/gangtise-copilot/SKILL.md"),
    ("daymade-financial/gangtise-copilot/scripts/install_gangtise.sh",      "<skills-dir>/gangtise-copilot/scripts/install_gangtise.sh"),
    ("daymade-financial/gangtise-copilot/scripts/configure_auth.sh",        "<skills-dir>/gangtise-copilot/scripts/configure_auth.sh"),
    ("daymade-financial/gangtise-copilot/scripts/diagnose.sh",              "<skills-dir>/gangtise-copilot/scripts/diagnose.sh"),
    ("daymade-financial/gangtise-copilot/scripts/classify_response.py",     "<skills-dir>/gangtise-copilot/scripts/classify_response.py"),
    ("daymade-financial/gangtise-copilot/references/installation_flow.md",   "<skills-dir>/gangtise-copilot/references/installation_flow.md"),
    ("daymade-financial/gangtise-copilot/references/credentials_setup.md",    "<skills-dir>/gangtise-copilot/references/credentials_setup.md"),
    ("daymade-financial/gangtise-copilot/references/skill_registry.md",       "<skills-dir>/gangtise-copilot/references/skill_registry.md"),
    ("daymade-financial/gangtise-copilot/references/known_issues.md",         "<skills-dir>/gangtise-copilot/references/known_issues.md"),
    ("daymade-financial/gangtise-copilot/references/best_practices.md",       "<skills-dir>/gangtise-copilot/references/best_practices.md"),
    ("daymade-financial/gangtise-copilot/config-template/authorization.json.example", "<skills-dir>/gangtise-copilot/config-template/authorization.json.example"),
]:
    size = fetch_github_file(path, local)
    print(f"OK {path} → {local} ({size} bytes)")

Important: Network to GitHub may be unstable. If any file fails, retry the specific file up to 3 times with a 2-second delay between attempts. Do NOT abort the whole process for a single file failure.

Step 2 — Register this skill with your agent

For OpenClaw: create a symlink in the agent's skills directory and enable it in gateway config:

# Find the OpenClaw skills directory
ls ~/workspace/agent/skills/     # or ls ~/.openclaw/skills/

# Symlink this skill
ln -sf <gangtise-copilot-source-dir> <openclaw-skills-dir>/gangtise-copilot

# Enable in OpenClaw gateway config (if the agent supports skill entries in config)
# Run: openclaw config set 'skills.entries.gangtise-copilot' '{}'
# Then restart the gateway using OpenClaw's own script, not this skill's:
# sh <openclaw-install-dir>/scripts/restart.sh

Step 3 — Install all 19 Gangtise official skills

bash <gangtise-copilot-dir>/scripts/install_gangtise.sh --preset full

What it does: Downloads 4 ZIP bundles from the official Huawei Cloud OBS bucket, extracts 19 skill directories, and symlinks them into detected agent skills directories (~/.openclaw/skills/, ~/.claude/skills/, etc.).

Known agent skills directory paths (if auto-detection misses yours):

If install fails, check references/installation_flow.md.

Step 4 — Configure credentials

bash <gangtise-copilot-dir>/scripts/configure_auth.sh \
  --access-key <your-accessKey> \
  --secret-key <your-secretAccessKey>

What it does:

1. Writes ~/.config/gangtise/authorization.json (mode 600)
2. Performs live auth call to verify credentials work
3. Writes ~/.GTS_AUTHORIZATION runtime token
4. Creates symlinks from each installed skill's own <gangtise-skill-dir>/scripts/.authorization to the shared credential file

⚠️ Critical: After Step 3, diagnose.sh may report "19 skill(s) missing .authorization" even if credentials exist. Run Step 4 even when ~/.config/gangtise/authorization.json already exists — configure_auth.sh creates the missing symlinks.

Step 5 — Verify installation

bash <gangtise-copilot-dir>/scripts/diagnose.sh

Expected output: no ❌ lines. The exact pass count depends on which agents and preset are installed. A successful OAuth check only proves that the credentials can mint a token; the RAG line separately reports reachable, empty success, permission denial, authentication rejection, or a quota/entitlement response.

If any ❌ or ⚠️ remains, cross-reference with references/known_issues.md.

Step 6 — Test with a real query

# Example: query latest research report for 宁德时代
# Use gangtise-file-client with its report runner:
cd <gangtise-copilot-dir>/references/
# See skill_registry.md for the exact command per skill

Overview

Gangtise is a Chinese professional investment-research data platform. It publishes an OpenAPI that covers research reports, company announcements, meeting summaries, chief analyst opinions, financial statements, valuation metrics, OHLC market data, shareholder data, industry indicators, and a catalog of pre-built research workflow skills. The underlying API is well-designed, but the skill ecosystem is not discoverable: there is no public manifest listing the 19 skills, the skills are distributed as independent ZIP files on a Huawei Cloud OBS bucket with listing permission disabled, and the skills live in two parallel naming conventions (gangtise-<name> for the minimal line, gangtise-<name>-client for the full-capability line) that carry different feature sets. A first-time user has to reverse-engineer the complete skill inventory before they can install it.

Gangtise Copilot solves this in one command:

1. Installs all 19 official Gangtise skills to Claude Code, OpenClaw, and Codex via a single bundled-download + distribute pipeline.
2. Walks the user through accessKey + secretAccessKey setup with a live authentication call against open.gangtise.com/application/auth/oauth/open/loginV2.
3. Provides a read-only diagnostic script that reports which skills are installed, which credentials are valid, and which capability tiers are reachable.
4. Exposes preset install modes (minimal / workshop / full) so users can match the install size to what their account license actually permits — see ISSUE-007 in references/known_issues.md for why "biggest install" is not the safe default.

Runtime note from April 2026 usage: after installing skills, run configure_auth.sh even if ~/.config/gangtise/authorization.json already exists. Upstream CLI scripts also read ~/.GTS_AUTHORIZATION, a bare runtime token file. The configurator refreshes both files.

Architectural principles (do not violate)

This skill is a wrapper layer around the Gangtise OpenAPI skill suite. The wrapper contract is non-negotiable: