SKILLEMALL.ai
GitHub ↗ RU Sign in

BB openspec-archive-change

Archive a completed OpenSpec change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete. Also use when the user says "openspec archive" or "opsx archive".

jamro/tiny-engineer Agent Skills author: jamro NOASSERTION 1 file body ≈ 4 033 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Archive a completed OpenSpec change in the experimental workflow.

As a process B 71/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

ProcedureData and analyticsAI and agentsWriting and documentstype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
B
71/100
Nearly there
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

The same skill appears in 1 more place: tiny-engineer

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 71/100

    • 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
    • 70Execution cost. Instruction body is 4033 tokens
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 60 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 6 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (11 tags): a typed call is more reliable

    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)
    • +4Structure: 0 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • -5Long text without headings
    • -5TODO / placeholder text left in the skill
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 222: enough signal without eating the budget
    • +3Step-by-step instructions: 60 items
    • +4Has examples (4 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.