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BD m365-spam-manager

Microsoft 365 spam folder manager for Outlook/Exchange mailboxes. Automatically analyzes junk/spam emails, calculates a suspicious score based on structural patterns (missing unsubscribe links, poor language, suspicious domains, wrong character sets, etc.), and helps clean up the junk folder. Supports review mode (default) where user approves each action, and automatic mode for batch processing. Works with shared mailboxes via --mailbox flag. Related keywords: Outlook, Exchange Online, spam filter, junk email, phishing, email security. **Token cost:** ~500-1.5k tokens per use.

modbender/skill-library-mcp Agent Skills author: modbender MIT 9 files body ≈ 609 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Microsoft 365 spam folder manager for Outlook/Exchange mailboxes.

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerOutlookSecuritytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
81
Run on models
none yet
Process rating
D
43/100
Unfinished process
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:77
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…xlQ+qhZu…XDg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:104
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…Acw+aHh4…d9e/hbIXq980/1QJg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:146
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…q1F+ppbRo70+YeaD…NPN+GD6b…CXQ==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:166
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…8CM+MzKM…4lA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:178
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha512-+NYs2QeMWy+GWFO…UmJ+93Q5…iX3/fpC6afS8Dhb/gz7R7eg==",
      detector

    Files scanned: 9. 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 43/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 609 tokens

    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
    • -33 of 6 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 583: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.