SKILLEMALL.ai

BD memory-sync

Use when preserving, searching, reviewing, or exporting user-owned agent memory across OpenClaw, Codex, Claude, OpenCode, Hermes, Qoder, Obsidian, and Git. Inputs are local memory/chat stores and handoff summaries; outputs are Obsidian sources, memory indexes, context/profile packs, skill inventories, and optional Git sync. Prefer after native agent memory/candidate extraction. Do not use for code debugging, unrelated backups, cloud memory, or temporary notes without durable value.

ClawHub Agent Skills author: Wildprogrammer v1.0.3 MIT-0 9 files body ≈ 10 564 tokens Open the sourceclawhub.ai analyzed 23 h ago

Inputs are local memory/chat stores and handoff summaries; outputs are Obsidian sources, memory indexes, context/profile packs, skill inventories, and…

As a process D 46/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerObsidianSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 10564 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 29, 32, 155, 428): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Consistency. Frontmatter name (memory-sync) differs from the folder (agent-memory-sync)
  • 40Execution cost. Instruction body is 10564 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 85Steps. 120 steps, 1 vague phrases
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (23 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
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 486: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 120 items
  • +4Has examples (35 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This skill is not clearly malicious, but it needs review because it can collect and persist broad local agent history, rules, configuration, and skill inventories into an Obsidian vault and optionally Git.
LLM: suspicious (high) · 28 Jun 2026