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AC devops-bridge

Unified developer operations bridge connecting GitHub, CI/CD (GitHub Actions), Slack, Discord, and issue trackers (Linear, Jira, GitHub Issues) into cross-tool automated workflows. Sends context-rich CI failure notifications to Slack with failing test details, tracks PR review lifecycle with escalating reminders, generates daily dev standup summaries, syncs issue status when PRs are merged, detects flaky tests, and monitors repository health. Use this skill for: PR review reminders, CI build alerts, "what happened in my repos", "any failing builds", "who needs a review", dev team standup summary, deploy notifications, repository monitoring, connecting GitHub to Slack, linking PRs to Jira/Linear tickets, code review tracking, merge conflict alerts, or any request to bridge development tools together. If the user mentions GitHub AND Slack (or any two dev tools) together, this skill connects them.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 718 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Unified developer operations bridge connecting GitHub, CI/CD (GitHub Actions), Slack, Discord, and issue trackers (Linear, Jira, GitHub Issues) into…

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSlackDiscordGitHubJiraInfrastructureSoftware developmentOperations and projectstype 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 0

    ✓ No critical or high findings

    Files scanned: 1. 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 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 85Steps. 40 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1718 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 907: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 40 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.