DD Privora · 数据驱动投资工作流平台 for AI Agents
Privora · AI Agent 投资工作流平台 — Bearer Token 即接入 /agent/skills/execute 通用 dispatcher,覆盖 A 股/港股/美股/黄金/基金/财报数据 + Python 回测(含 sandbox)+ 模拟交易 + 组合归因(α/β TWR)+ 云端告警 + 流程编排。Hermes / Claude / GPT / OpenClaw 全兼容。
Privora · AI Agent 投资工作流平台 — Bearer Token 即接入 /agent/skills/execute 通用 dispatcher,覆盖 A 股/港股/美股/黄金/基金/财报数据 + Python 回测(含 sandbox)+ 模拟交易 + 组合归因(α/β TWR)+ 云端告警 +…
As a process D 41/100 · Unfinished process — References files that are not bundled: CHANGELOG.md, lg-data-demo.gif, ../mcp-server/README.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 5
✓ No critical or high findings
Medium and low: 5
-
low Exfiltration
net-credential-usescripts/lg_agent_exec.sh:296Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)LG_AGENT_TOKEN_ESC="$(_curl_config_escape "$LG_AGENT_TOKEN")" || exit 1
detector -
low Exfiltration
net-credential-usescripts/lg_agent_list.sh:280Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)LG_AGENT_TOKEN_ESC="$(_curl_config_escape "$LG_AGENT_TOKEN")" || exit 1
detector -
low Exfiltration
net-credential-useSKILL.md:262Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)curl -H "Authorization: Bearer $LG_AGENT_TOKEN" \
security skill -
low Exfiltration
net-credential-useSKILL.md:270Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)curl -H "Authorization: Bearer $LG_AGENT_TOKEN" \
security skill -
low Exfiltration
net-credential-useSKILL.md:279Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)curl -H "Authorization: Bearer $LG_AGENT_TOKEN" \
security skill
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 35682 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: CHANGELOG.md - warning
missing-refreference to a missing file: lg-data-demo.gif - warning
missing-refreference to a missing file: ../mcp-server/README.md - warning
missing-refreference to a missing file: scripts/lg_agent_approval.sh - note
frontmatter-keyunknown frontmatter key "title" - note
frontmatter-keyunknown frontmatter key "updatedAt" - note
frontmatter-keyunknown frontmatter key "keywords" - note
edit-residuethe text marks something as outdated (lines 601, 1232, 1265, 1280, 1300, 1530): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 41/100
- 0Tools and files. 4 referenced file(s) missing: CHANGELOG.md, lg-data-demo.gif, ../mcp-server/README.md
- 0Result and completion. Does not say what the result is
- 10Execution cost. Instruction body is 35682 tokens: crowds the task out of the window
- 40Consistency. Frontmatter name (Privora · 数据驱动投资工作流平台 for AI Agents) differs from the folder (privora-cn-quant)
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 243 steps, 1 vague phrases
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (14 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2284 emoji in the instructions: noise for the model
- +2Single-language instructions
- +3Description length 201: enough signal without eating the budget
- +4Structure: 116 headings
- +3Step-by-step instructions: 243 items
- +4Has examples (52 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.