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BD pi-history-ingest

Ingest Pi coding-agent session history into Obsidian as distilled knowledge. Use for importing or mining ~/.pi/agent/sessions or Pi conversation logs; use wiki-agent for targeted topic-only recall.

Ar9av/obsidian-wiki Agent Skills author: Ar9av MIT 1 file body ≈ 3 484 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Ingest Pi coding-agent session history into Obsidian as distilled knowledge.

As a process D 46/100 · Unfinished process — References files that are not bundled: references/pi-data-format.md

ProcedureObsidianAI 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
Unfinished process
References files that are not bundled: references/pi-data-format.md
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
20
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: references/pi-data-format.md

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: references/pi-data-format.md
  • 0Tools and files. 1 referenced file(s) missing: references/pi-data-format.md
  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 8 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 88 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3484 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 197: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 88 items
  • +4Has examples (11 code blocks)

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