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BF create-artifact

Register a plan artifact via the MCP backlog server. Use when you produce a document or report that downstream agents or worktree-isolated environments need to retrieve — feature-context, codebase-analysis, architect, T0-baseline, TN-verification, or research artifacts. Triggers include "store an artifact", "register a plan artifact", "write a report to the backlog", "upload artifact content".

Jamie-BitFlight/claude_skills Agent Skills author: Jamie-BitFlight MIT 1 file body ≈ 1 331 tokens Open the sourcegithub.com↗ analyzed 8 d ago

Register a plan artifact via the MCP backlog server.

As a process F 29/100 · No process to follow — References files that are not bundled: ../../dh_core/artifact_registry.py, ../../docs/artifact-registry.md

GeneratorData and analyticsSoftware developmentAI and agentstype 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%
80
Run on models
none yet
Process rating
F
29/100
No process to follow
References files that are not bundled: ../../dh_core/artifact_registry.py, ../../docs/artifact-registry.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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

  • warning missing-ref reference to a missing file: ../../dh_core/artifact_registry.py
  • warning missing-ref reference to a missing file: ../../docs/artifact-registry.md

Process rating: all ten parameters 29/100

Will not run. References files that are not bundled: ../../dh_core/artifact_registry.py, ../../docs/artifact-registry.md
  • 0Tools and files. 2 referenced file(s) missing: ../../dh_core/artifact_registry.py, ../../docs/artifact-registry.md
  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 75Steps. 3 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1331 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 396: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.