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BC jsp-376

Knowledge pack synthesized from JSP 376 Defence Acquisition Safety Policy V1.1 (April 2024, Ministry of Defence, Open Government Licence v3.0): acquisition safety requirements, safety artefacts, and their application across the standard acquisition lifecycle. Covers the policy frame and legislative baseline, SRO and User responsibilities, safety management and safety requirements, test and evaluation and the safety case, supervision and approvals decision support, and the seven lifecycle phases. SCOPE LIMITS: single-source (JSP 376 V1.1); MOD policy and guidance, not statute; builds on JSP 815 and cites JSP 655, neither reproduced here (use jsp-815 for the SMS); Chapter 4 (Non-Standard Acquisition) is unpublished in V1.1 and is not in this pack; no DEF-STAN text (Def Stan 00-056 is named, not quoted); no other JSP reproduced. Reconstructed reference notes, not MOD guidance, and no official status.

jgsystemsconsulting/jgs-se-knowledge-packs Agent Skills author: jgsystemsconsulting 13 files body ≈ 2 109 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Knowledge pack synthesized from JSP 376 Defence Acquisition Safety Policy V1.1 (April 2024, Ministry of Defence, Open Government Licence v3.0): acquisition…

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

ProcedureData and analyticsAI and agentsSecuritytype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
58/100
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: 13. 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
    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2109 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

    • +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 910: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 35 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.