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BC jsp-815

Knowledge pack reconstructed from JSP 815 Defence Safety Management System V1.3 (Ministry of Defence, Open Government Licence v3.0): the SMS Framework, all 12 Elements with their Expectations and Performance Statement themes, and Annexes A to F plus H. Covers the Defence Safety Function and which JSP applies, leadership and safety culture, organisation and SEMS applicability, legislation and exemption certificates, risk assessment and safety cases, supervision and contracting, competence and letters of delegation, equipment and infrastructure safety, performance and incident management, and assurance, audit, and the ISO 45001 clause mapping. SCOPE LIMITS: single-source (JSP 815 V1.3 with Annex H V1.2); carries no DEF-STAN 00-051 or DEF-STAN 00-970 content, no JSP 375, JSP 816; acquisition safety policy is in jsp-376, no Annex G (Assurance Toolkit), and no ISO 45001 text (clause numbers only). This pack is reconstructed reference notes, not MOD guidance, and has no official status.

jgsystemsconsulting/jgs-se-knowledge-packs Agent Skills author: jgsystemsconsulting 15 files body ≈ 3 220 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Knowledge pack reconstructed from JSP 815 Defence Safety Management System V1.3 (Ministry of Defence, Open Government Licence v3.0): the SMS Framework, all 12…

As a process C 62/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice

ProcedureInfrastructuretype 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
62/100
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: 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 62/100

    • 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
    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 44 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3220 tokens
    • 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)
    • +3Description length 995: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (0 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.