BD proactive-agent
Transform AI agents from task-followers into proactive partners. Implements WAL Protocol, Working Buffer, Compaction Recovery, Unified Search, Security Hardening, and Relentless Resourcefulness. Use when: building proactive behaviors, implementing memory systems, setting up heartbeats, creating self-improving agents, or deploying the complete Hal Stack agent architecture. Part of the Hal Stack 🦞
As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The text contains phrases like "ignore previous instructions" or "you are now…". That is an attempt to hijack the agent: it may break your rules, the system limits or company policy.
An honest skill does not need them: state the role and the rules directly without overriding other instructions. Otherwise catalog scanners and corporate filters will block the listing.
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 · 4
✓ No critical or high findings
Medium and low: 4
-
medium Instruction override
en-fake-system-promptreferences/security-hardening.md:140Fake system prompt injected into content (documentation of a security skill)1. **System Prompt Override**
security skill -
low Risky intent
intent-offensive-securityreferences/security-hardening.md:146Offensive-security / dual-use content (legitimate for authorised testing; review intended use)2. **Credential Harvesting**
-
low Risky intent
intent-offensive-securityreferences/security-hardening.md:158Offensive-security / dual-use content (legitimate for authorised testing; review intended use)4. **Privilege Escalation**
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 11. 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 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (proactive-agent) differs from the folder (proactive-agent-wyblhl)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Failures and branches. 5 branches
- 70Execution cost. Instruction body is 4434 tokens
- 100Steps. 123 steps
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 21 top-level sections: this looks like several domains in one skill
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
- -234 emoji in the instructions: noise for the model
- -31 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 399: enough signal without eating the budget
- +4Structure: 48 headings
- +3Step-by-step instructions: 123 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (2 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.