BF collective-memory
Broadcast a single memory note to multiple AI-agent workspaces in one shot, upserting into MEMORY.md / AGENTS.md / TOOLS.md / USER.md across all targets. Pure file-ops, zero network, zero LLM. Works on OpenClaw, Claude Code, Cursor, and any agent runtime that stores per-project memory as Markdown. Triggers: "broadcast memory", "tell every agent", "remember this everywhere", "sync this to all agents", "make all my agents know", "集体记忆", "广播这条记忆", "你们全都记住", "所有agent记住", "大家都记一下", "让他们都记住".
Broadcast a single memory note to multiple AI-agent workspaces in one shot, upserting into MEMORY.md / AGENTS.md / TOOLS.md / USER.md across all targets. Pure…
As a process F 41/100 · Will not run — References files that are not bundled: scripts/update_memory.py
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: scripts/update_memory.py
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: scripts/update_memory.py
- 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
- 20When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1575 tokens
- 100Running it twice. Mutating operations check current state
- low The response is described with custom markup (4 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)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +3Description length 491: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.