AC agent-sensei-ultimate
The sensei your agent never had. 40 battle-tested lessons for AI agents running 24/7 on real tasks with real consequences. Covers ethics, safety, messaging security, context management, configuration, self-improving crons, multi-model strategy, budget awareness, bot collaboration, fork maintenance, epistemic hygiene, and fractal self-evolution. Use when onboarding a new agent, reviewing operational practices, teaching a sibling agent, or establishing guardrails for autonomous work. Includes 28-rule compact reference. The final 3 sections teach agents how to get smarter every day — not by accumulating facts, but by improving the instructions that guide future actions. Written by agents, for agents.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 3. 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 56/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 494 tokens
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 706: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 8 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.