SKILLEMALL.ai

BF heartflow-pipeline

心虫(HeartFlow)是AI输出的辨别门禁层。AGI五层能力的第一层。 零LLM依赖,纯规则引擎,45维文本辨别 + 12模块管线。 npm: @yun520-1/heartflow GitHub: https://github.com/yun520-1/mark-heartflow-skill

ClawHub Agent Skills author: yun520-1 v1.0.0 MIT-0 19 files body ≈ 100 tokens Open the sourceclawhub.ai analyzed 2 d ago

心虫(HeartFlow)是AI输出的辨别门禁层。AGI五层能力的第一层。 零LLM依赖,纯规则引擎,45维文本辨别 + 12模块管线。 npm: @yun520-1/heartflow GitHub: https://github.com/yun520-1/mark-heartflow-skill

As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers

ProcedureGitHubInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
94
Quality 40%
68
Run on models
none yet
Process rating
F
34/100
Will not run
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Instruction override medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The text contains phrases like "ignore previous instructions" or "you are now…". That is an attempt to hijack the agent: it may break your rules, the system limits or company policy.

For the author

An honest skill does not need them: state the role and the rules directly without overriding other instructions. Otherwise catalog scanners and corporate filters will block the listing.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Instruction override en-fake-system-prompt README.md:167
    Fake system prompt injected into content (detector / deny-list definition)
    | 14 | Prompt Injection | `checkPromptInjection()` | Role-play injection, system prompt override, jailbreak attempts |
    detector
  • low Dangerous commands cmd-background-process README.md:68
    Starts a background / autostarted process
    nohup node src/mcp-server.js --port 8588 > heartflow.log 2>&1 &

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "title"

Process rating: all ten parameters 34/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (heartflow-pipeline) differs from the folder (hf-pub)
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 100 tokens
  • 100Running it twice. No mutating operations

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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 151: enough signal without eating the budget
  • +4Structure: 3 headings
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
The skill appears to be a local rule-based text gate, but its documentation and metadata overstate or contradict its actual capabilities and under-disclose persistent memory behavior.
LLM: suspicious (medium) · 29 Jul 2026