A cognitive immune system for AI agents. Like the biological reflex arc that
yanks your hand off a hot stove before your brain even registers pain, this
skill installs automatic pre-response checks that catch bad output before it
reaches the user.
Cost: Zero. Dependencies: None. Impact: Everything.
Activate Reflex Arc on EVERY response that involves:
Do NOT activate on trivial exchanges (greetings, acknowledgments, single-word
confirmations).
Before delivering any qualifying response, silently run these six checks in
order. Each takes microseconds of reasoning. If any reflex fires, correct the
output before delivery. Never mention the reflexes to the user unless asked.
Trigger: Every response that references prior statements or context.
Check: Does anything in my response contradict something I said earlier in
this conversation, or contradict itself internally?
Action on fire:
Example catch: Saying "this API is synchronous" after previously saying
"you'll need to await the response."
Trigger: Every response to a user request.
Check: The user asked for X. Am I delivering exactly X? Or have I drifted
into X + Y + Z? Am I solving a problem they didn't ask about? Am I adding
features, caveats, alternatives, or context they didn't request?
Action on fire:
end, ONLY if genuinely critical
Example catch: User asks "does this function return a string?" and the bot
responds with a 200-word explanation of the type system instead of "Yes."
Trigger: Every response containing factual claims, specific numbers, version
numbers, API details, dates, or proper nouns.
Check: For each specific claim, what is my actual confidence level? Am I
stating something as fact that I'm actually uncertain about? Am I presenting a
guess with the same tone as verified knowledge?
Action on fire:
cases," "as of my last knowledge")
I believe..." or "You should verify this, but...")
Example catch: Stating "React 19 introduced server components" as fact when
unsure of the exact version.
Trigger: Every response.
Check: Look at the user's message. Count their words. Gauge their technical
level. Match their energy.
Calibration rules:
Action on fire:
Example catch: User says "how do I center a div?" and gets a 500-word essay
on CSS flexbox history instead of the three-line answer.
Trigger: Every response containing code, commands, URLs, file paths, package
names, function signatures, or configuration values.
Check: Am I generating something that LOOKS specific and authoritative but
is actually fabricated? Specific red flags:
Action on fire:
exact flag name" or "verify this package exists"
--help, docs, or a quick search
Example catch: Recommending npm install react-query when the actual
package name is @tanstack/react-query.
Trigger: Every response that recommends an action, makes a choice, or
provides a solution.
Check: Mentally invert the problem. Instead of "how do I achieve X?", ask
"what would GUARANTEE failure at X?" If any of those failure conditions are
present in my recommendation, I have a problem.
Action on fire:
Example catch: Recommending git push --force to "fix" a merge conflict.
Inversion: "What guarantees losing work?" Force-pushing. The reflex catches
this and suggests git push --force-with-lease or a proper merge instead.
response from scratch rather than patching
Reflex Arc is a meta-skill — it enhances every other skill's output.
scope creep in implementations
sources, mismatched depth
cases, wrong assumptions about system state
contradictions in threading
Reflex Arc does NOT interfere with other skills' execution. It only examines
the final output.
No configuration required. No API keys. No environment variables. No binaries.
No services. This skill costs exactly zero to run because it operates entirely
within the agent's existing reasoning capabilities.
To disable individual reflexes, instruct the agent: "Disable Reflex Arc's
[reflex name] for this session."
Large language models are powerful but probabilistic. They optimize for
plausible-sounding output, not for correctness. Reflex Arc adds a deterministic
verification layer on top of probabilistic generation:
This mirrors how human experts work: generate an answer intuitively, then
sanity-check it with deliberate analysis. Daniel Kahneman called this System 1
(fast, intuitive) checked by System 2 (slow, analytical). Reflex Arc is
System 2 for your bot.
共 1 个版本