SKILLEMALL.ai

AC codecast

Stream coding agent sessions (Claude Code, Codex, Gemini CLI, etc.) to a Discord channel in real-time via webhook. Use when invoking coding agents and wanting transparent, observable dev sessions — no black box. Parses Claude Code's stream-json output into clean formatted Discord messages showing tool calls, file writes, bash commands, and results with zero AI token burn. Use when asked to "stream to Discord", "relay agent output", or "make dev sessions visible".

modbender/skill-library-mcp Agent Skills author: modbender MIT 15 files · 6 scripts body ≈ 900 tokens Open the sourcegithub.com analyzed 2 d ago

Stream coding agent sessions (Claude Code, Codex, Gemini CLI, etc.) to a Discord channel in real-time via webhook. Use when invoking coding agents and wanting…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationDiscordSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
90
Run on models
none yet
Process rating
C
53/100
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration exfil-webhook-url references/setup.md:25
      Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
      echo "https://discord.com/api/webhooks/<ID>/<TOKEN>" > {baseDir}/scripts/.webhook-url
      placeholder
    • low Exfiltration exfil-webhook-url scripts/dev-relay.sh:143
      Webhook / callback URL commonly used for exfiltration (verify the destination) (the skill's own vendor host; quoted — discussed, not commanded)
      [ -z "$WEBHOOK_URL" ] && { echo "❌ Error: .webhook-url not found in $SCRIPT_DIR" >&2; echo "  Create it: echo 'https://discord.com/api/webhooks/ID/TOKEN' > $SCRIPT_DIR/.webhook-url" >&2; exit 1; }
      vendor-hostquoted

    Files scanned: 15. 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 53/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 900 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (7 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -37 of 8 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 467: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.