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CD Token Alert Skill

🚨 Monitor session tokens and get alerts at 75%/90%/95%

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 33 files · 5 scripts body ≈ 1 105 tokens Open the sourcegithub.com↗ analyzed 2 d ago

🚨 Monitor session tokens and get alerts at 75%/90%/95%

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureTelegramGitHubData and analyticstype 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
C
70/100
safety, quality, tests
Safety 60%
70
Quality 40%
71
Run on models
none yet
Process rating
D
41/100
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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

  • high Dangerous commands cmd-persistence scripts/setup-notifications.sh:26
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$PLIST_DST"
Medium and low: 4
  • medium Dangerous commands cmd-persistence scripts/setup-notifications.sh:17
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    PLIST_DST="$HOME/Library/LaunchAgents/com.clawdbot.token-alert.plist"
    code literal
  • medium Dangerous commands cmd-persistence scripts/setup-notifications.sh:36
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    echo "  Start:  launchctl load $PLIST_DST"
    code literal
  • low Exfiltration exfil-secret-in-url research/multi-provider-research-2026-01-27.md:153
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (destination is a well-known publishing service; quoted — discussed, not commanded)
    curl "https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=…" \
    known servicequoted
  • low Exfiltration net-credential-use research/multi-provider-research-2026-01-27.md:153
    Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)
    curl "https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=…" \
    known service

Files scanned: 33. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

Process rating: all ten parameters 41/100

  • 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
  • 40Consistency. Frontmatter name (Token Alert Skill) differs from the folder (token-alert)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 38 steps
  • 100Execution cost. Instruction body is 1105 tokens
  • 100Running it twice. Mutating operations check current state
  • low 12 top-level sections: this looks like several domains in one skill

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 55: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • -310 of 12 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.