Migrating Prompts From Claude/GPT To Hermes: Gotchas

Most prompts that work on Claude or GPT need adjustment to work well on Hermes. Knowing what to change — and what not to bother with — saves a week of trial and error.

9 min · Reviewed 2026

What porting really involves

A prompt is not pure logic — it is logic plus model-specific phrasing that the original model is good at following. Migrating it is part translation, part re-tuning, part discovering which parts of the original were actually doing work. Plan for each prompt to need a few rounds of iteration before it matches the source-model output.

Common gotchas, by source model

Source model trait	What it depends on	Hermes adjustment
Claude XML tags (<thinking>, <answer>)	Anthropic's tag conventions	Replace with plain prose sections and explicit format directives
Claude polite-and-thorough tone	Anthropic tuning	May come out shorter and blunter; tune system prompt for length
GPT step-by-step reasoning instructions	OpenAI's chain-of-thought training	Works on Hermes but may need explicit 'think step by step' more often
GPT JSON mode reliance	OpenAI strict-json infrastructure	Replace with grammar-constrained decoding or schema-with-examples
GPT tool-call format	OpenAI's tools schema	Convert to Hermes's documented function-call grammar
Memory / Custom Instructions	OpenAI's persistent state	Move stable parts into Hermes system prompt; rebuild the rest

Things that usually port for free

Plain task descriptions ('summarize this article in 100 words').
Schema-locked output requests with one example.
Anti-rules ('do not include code fences', 'do not preamble').
Domain-specific glossaries and definitions.
Few-shot examples — these often help Hermes more than they helped the source model.

Things that need real work

Tool-using prompts — different grammar, different harness expectations.
Long persona prompts — Hermes responds in kind, sometimes more than you wanted.
Anything depending on memory or persistent state — you build the state layer yourself.
Anything depending on a specific provider feature (web search, image gen, code interpreter) — those become separate components.

Migration workflow

Pick the highest-value prompt in your library.
Snapshot its current output on the source model for 10 representative inputs.
Translate to Hermes using the gotchas table.
Run on the same 10 inputs. Compare line by line.
Iterate on the system prompt until Hermes outputs are equivalent or you accept the gap.

Applied exercise

Open one prompt that you know works well on Claude or GPT.
Identify every line that depends on a model-specific feature using the gotchas list.
Rewrite those lines for Hermes.
Run on three sample inputs and compare. Note which adjustments mattered most for your use case.

The big idea: porting prompts is a translation, not a copy. Mind the gotchas, evaluate honestly, and trim what is no longer carrying weight.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-hermes-prompt-migration-creators

What is the main idea of "Migrating Prompts From Claude/GPT To Hermes: Gotchas"?
1. Most prompts that work on Claude or GPT need adjustment to work well on Hermes.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Migrating Prompts From Claude/GPT To Hermes: Gotchas"?
1. format differences
2. prompt migration
3. tool grammar
4. tone calibration
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. Plain task descriptions ('summarize this article in 100 words').
4. Treat the AI output as automatically correct
What should a careful learner remember about "The eval-set discipline saves you"?
1. Use "The eval-set discipline saves you" as a reminder to verify the AI output before anyone relies on it.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use AI for drafting and comparison, but verify before publishing or relying on it.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about prompt migration be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about prompt migration.
Which action would help you apply "Migrating Prompts From Claude/GPT To Hermes: Gotchas" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Treat the AI output as automatically correct
4. Schema-locked output requests with one example.

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