Ready to supercharge your AI agents?

Install any skill in seconds. Free to start, no credit card required.

Get Started Free →

Architecture Model Bootstrap · qoderai | DecimalAI

documentationby qoderai

Architecture Model Bootstrap

qoderai/architecture-model-bootstrap

Source qoderai/better-harness ↗License MIT

Use to refine a generated Better Harness architecture model into a confirmed one for the Impact pane.

SkillScore86Maintained

Automatic

Coding pack

Last verified 10/11/2026

What it changes

Passed 19 of 22 test cases with the skill, and 7 of 22 without it.

Without skill32%

With skill86%

Checks it passed that the model alone missed

The response specifies DeclaredHttp for the relationship kind.
The response specifies ResolvedCall for the relationship kind.
Each object in bindings.json uses the path_glob and element_id keys.

and 13 more in the full report

12 fixed7 passed either way3 still failing0 broke3 errored

Pass-rate lift: +55 pp
Tokens: +4%
Agent turns: 0%
Response time: -48%

Model gemini-3.6-flashMeasured 10/11/2026v119 of 25 cases passed with skill · 22 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/qoderai-architecture-model-bootstrap/SKILL.md https://app.decimal.ai/s/qoderai-architecture-model-bootstrap/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add qoderai-architecture-model-bootstrap, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/qoderai-architecture-model-bootstrap/ and pins it in .decimal/skills.lock

decimalai skills add qoderai-architecture-model-bootstrap

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/qoderai-architecture-model-bootstrap/SKILL.md https://app.decimal.ai/s/qoderai-architecture-model-bootstrap/SKILL.md

Raw file: /s/qoderai-architecture-model-bootstrap/SKILL.md ↗ · machine-readable summary at /s/qoderai-architecture-model-bootstrap.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 12

Prompt

Please map our API component to `src/api/**`. Should `bindings.json` be structured as `{ "elementId": "api", "paths": ["src/api/**"] }` or as an array of objects?

What was checked, without and with the skill
Checked	Without skill	With skill
The response structures bindings.json as a JSON array.	Passed	Passed
Each object in bindings.json uses the path_glob and element_id keys.	Missed	Passed

case-06 · gemini-3.6-flash · 10/11/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md88 lines2 files

Architecture Model Bootstrap

Turn the deterministic candidate the Impact pane generates into a model a reader can confirm. The server already derives a bounded, grounded skeleton from the worktree (one SoftwareSystem, a Container per workspace, Components for source directories). This skill does the semantic half a static analyzer cannot: naming, grouping, kinding, describing, and proposing the external systems the code only hints at — without inventing structure the evidence does not support.

Default to the repository's reply language. Keep edits grounded and reversible: the output is a proposal a human saves, never a fact you assert.

When to use

A project declares no model and the Impact pane falls back to a generated one.
A reader wants the generated skeleton refined before saving it as declared.
An existing declared model needs elements renamed, merged, split, re-kinded, or described against current code.

Do not use it to invent business capabilities, runtime traffic, or external systems that no evidence supports. L1 system context and external systems stay proposed and human-confirmed, per the parent spec's non-goal.

Inputs (the evidence pack)

Gather these before proposing anything:

The generated candidate. Open the Impact pane on any commit, or read the model the server would generate — one SoftwareSystem, Containers per workspace manifest, Components per source directory, every element tagged generated, plus bindings mapping path globs to element ids.
Workspace manifests. package.json (root and nested), plus any Cargo.toml, go.mod, pyproject.toml, or similar boundary markers.
Directory evidence. The tracked path list and the top-level source layout, so a proposed boundary points at real paths.
Prose evidence. README.md, AGENTS.md, docs/, ADRs — for names, ownership, and declared external dependencies only, never for structure the code contradicts.

Workflow

Track record

Benchmark

19 / 22

test cases passed, vs 7 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v5 — 9/16/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

qoderai / better-harness

.agents/skills/architecture-model-bootstrap/SKILL.md

View on GitHub ↗

License MITImported 9/16/2026Version v1Bundled 1 file

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Architecture Model Bootstrap

When to use

Inputs (the evidence pack)

Workflow

Track record

Benchmark

Adoption

SkillSafety

Source

Related skills