SKILLEMALL.ai

BC memory-palace

持久化记忆管理。Use when: 用户告诉你个人信息/偏好/习惯、需要记住项目状态/技术决策、完成任务后有可复用经验、用户说"记住""别忘了""下次注意"、需要回忆之前的对话内容。支持语义搜索和时间推理。

ClawHub Agent Skills author: 蓝宙 v1.8.5 MIT-0 53 files body ≈ 682 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
82
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Secrets in code secret-high-entropy-token package-lock.json:83
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…cAz+ivBu…Lvw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:168
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…IxX/wd5n…MGF+pv6g…i2Z+Wnj9/KjGz…4Eg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:202
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…BQM/qZ3R+9TEU…es4+qu1b…BFA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:219
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha512-8mL/vh8q…uJP+ZcVY…AJW+m0Et…WzA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:236
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…NES+HiD4…TOe+/2rdn…PWn/r/aAw==",
      detector
    • low Dangerous commands cmd-shell-rc scripts/check-vector-deps.cjs:161
      Writes to a shell startup file (string literal in code, not executed)
      log('   $ echo "export HF_ENDPOINT=https://hf-mirror.com" >> ~/.bashrc', 'blue');
      code literal

    Files scanned: 53. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 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
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 682 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)
    • +3Description length 103: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -35 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This memory skill mostly does what it says, but it needs review because it persistently stores personal data and can send raw memories to configured LLM providers without clear consent or privacy controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026