AF memory-system-sidecar
Operate, verify, rebuild, and debug the actual MemoryLab long-term memory sidecar that feeds `memory/ACTIVE_TASK_STATE.md` and `memory/LIVE_CONTEXT_PACKET.md`. Use when working on this repo’s implemented memory system: refreshing from session history, rebuilding indexes, running evals/tests, auditing milestone status, checking contamination boundaries, or inspecting memory artifacts under `memory-system/`, `memory/`, `history/`, and `scripts/context-refresh*`.
As a process F 41/100 · Will not run — References files that are not bundled: scripts/context-refresh*
How to improve
- 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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Operate, verify, rebuild, and debug the actual MemoryLab long-term… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: scripts/context-refresh*
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: scripts/context-refresh*
- 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
- 70When it triggers. States when to use, but not when not to
- 100Steps. 31 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 699 tokens
- 100Running it twice. No mutating operations
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 464: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.