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Agent config adapter

Skill jajupmochi/agent-harness/skills/agent-config-adapter

Adapt an existing agent configuration or plugin to a new agent or model route. Use when moving agent-harness or another agent setup between Claude Code, Codex, Gemini, Cursor, local models, or non-native model backends such as DeepSeek routed through another agent.From its SKILL.md

Install
npx -y skills add jajupmochi/agent-harness --skill agent-config-adapter

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.6 KB, 493 tokens by cl100k_base, as published. Nobody here has run it

agent-config-adapter

Use this workflow to port an existing agent configuration without dumping every rule into the target agent context.

Inputs to establish

  1. Source agent and config root.
  2. Target agent and target model route.
  3. Whether the model is native to the target agent or routed through a compatibility layer.
  4. Required capabilities: durable instructions, skills, hooks, MCP/tools, slash commands, subagents, browser/computer use, memories, and installers.
  5. Non-negotiable isolation constraints: what must not affect the original agent setup.

Adaptation steps

  1. Inventory the source configuration:
    • manifests
    • skills
    • hooks
    • rules/instructions
    • MCP/app/tool config
    • install scripts
    • templates
    • tests or validation scripts
  2. Research the target agent's current extension surfaces from local docs or official docs. For Codex, use the openai-docs Codex manual route.
  3. Build a mapping table: source item, target surface, required rewrite, verification method, and isolation risk.
  4. Choose the smallest target entrypoint:
    • instructions file for always-on repo rules
    • skill for reusable workflow
    • plugin for distribution
    • hook for lifecycle enforcement
    • MCP/app for live tools or private external data
  5. Implement target-specific wrappers. Keep shared source content as references so implicit skill metadata stays small.
  6. Verify structurally first, then run one realistic prompt per major workflow.

Model-route fallbacks

When the target model is not native to the agent, or implicit tool use is weak:

  • Prefer explicit skill invocation in user docs and default prompts.
  • Split long rule sets into small wrappers that name exactly which references to read.
  • Use scripts for deterministic checks instead of relying on the model to remember every invariant.
  • Require command output or file inspection before success claims.
  • Avoid hidden global instructions that the routed model may ignore.
  • Keep model-specific workarounds in the adapter skill, not in shared rules.

Deliverables

Every adaptation should leave:

  • A plan document with the mapping table and selected architecture.
  • Agent-specific manifest/config files.
  • A validation command or script.
  • Installation notes for the target agent.
  • A rollback note explaining which original agent files were not touched.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most project setup skills give in 493 tokens

Counted across 1,553 of the 3,091 authors here whose files we hold, read 2026-09-06

  • Write the configuration filein 36 of 1553
  • Create the directory structurein 35 of 1553, across 33 files
  • Verify the setupin 31 of 1553, across 28 files
  • Run the setup scriptin 30 of 1553, across 29 files
  • Pre-determine the required sample sizein 29 of 1553, across 12 files
  • Check if the configuration already existsin 29 of 1553
  • Document every testin 26 of 1553, across 10 files
  • Start with a hypothesisin 26 of 1553, across 11 files
  • Ask one question at a timein 22 of 1553
  • Test a single variable per testin 21 of 1553, across 9 files
  • Read product marketing context before asking questionsin 19 of 1553, across 8 files
  • Do not peek and stop earlyin 18 of 1553, across 7 files

Said here and by no other author read

  • Inventory the source configuration
  • Research the target agent extension surfaces
  • Build a mapping table
  • Choose the smallest target entrypoint
  • Implement target-specific wrappers
  • Verify structurally first

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.