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BC rail-signpost

Signpost (not a knowledge pack) for the railway RAMS and signalling assurance standards: EN 50126-1:2017 and EN 50126-2:2017 (both with A1:2024) for the RAMS process, EN 50128:2011 (A1:2020, A2:2020) for software for railway control and protection systems, and EN 50129:2018 and EN 50129:2026 for safety-related electronic systems for signalling, plus the free CSM regulations and ORR guidance that cover the risk-process need. Contains no source content: each row carries only the designation, title, edition, owner, redistributability status, and an official URL. Use when you need to identify, cite, or locate one of these documents. No in-repo pack covers these standards.

jgsystemsconsulting/jgs-se-knowledge-packs Agent Skills author: jgsystemsconsulting 2 files body ≈ 3 156 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Signpost (not a knowledge pack) for the railway RAMS and signalling assurance standards: EN 50126-1:2017 and EN 50126-2:2017 (both with A1:2024) for the RAMS…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureSecurityMarketingInfrastructuretype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "kind"
    • note edit-residue the text marks something as outdated (lines 76): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3156 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 676: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 9 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.