Создавайте AI-инструменты с Metkagram

01 · Intent → pattern

/api/v1/discovery.json

Идите от коммуникативной задачи к нужной поверхности и каноническим объектам.

02 · Pattern → tutor

/api/v1/patterns/{pattern-id}.json

Передавайте модели формулу, примеры, stable ID и canonical URL, а подачу адаптируйте под ученика.

03 · Recipes → workflow

/api/v1/ai-recipes.json

Используйте публичные сценарии как integration examples.

01 · integration recipe

Resolve a learner job to a reviewed Metkagram surface before retrieving content.

/api/v1/discovery.json

Lookup: {"surface_id":"reasoning-packs"}

• preserve the selected surface id
• explain why the surface matches the learner job
• continue only to canonical public objects

02 · integration recipe

Retrieve one canonical Pattern and keep its stable identity and provenance downstream.

/api/v1/patterns/clf051.json

Lookup: {"pattern_id":"CLF051"}

• preserve stable Pattern ID
• preserve canonical URL
• preserve dataset/version provenance
• do not rewrite the record as a newly invented Metkagram Pattern

03 · integration recipe

Retrieve a reviewed distinction and then a bounded practice decision for that same distinction.

/api/v1/contrasts.json → /api/v1/choice-drills.json

Lookup: {"contrast_id":"necessary-vs-not-enough","drill_id":"testing-required-not-guaranteed"}

• state the reviewed distinction before the exercise
• present the choice before feedback
• keep both stable Pattern IDs
• do not label the rejected option universally wrong

04 · integration recipe

Retrieve a reviewed ordered Route when the learner needs a sequence rather than one isolated Pattern.

/api/v1/reasoning-packs.json

Lookup: {"pack_id":"evidence-without-overclaiming"}

• preserve step order
• resolve referenced Patterns/Contrasts/Choices rather than copying new canonical content
• keep the Route ID and provenance

05 · integration recipe

Retrieve reviewed English and German forms that perform the same bounded reasoning job.

/api/v1/cross-language-map.json

Lookup: {"pattern_id":"CLF051"}

• keep the shared stable Pattern ID
• preserve both canonical language forms
• state that the mapping is functional rather than word-for-word equivalence
• keep provenance and canonical link

06 · integration recipe

Project one reviewed canonical language object into a bounded external spoken-practice task without adding speech-analysis claims or copying the corpus.

/api/v1/spoken-practice-handoffs.json

Lookup: {"handoff_id":"metkagram:spoken-practice:v1:pattern-evidence-without-overclaiming"}

• preserve handoff ID and canonical source ID/URL
• preserve source provenance, dataset version and rights references
• treat the prompt as one immutable user-requested practice snapshot rather than a corpus export
• leave recording, delivery feedback and speech evaluation to the external consumer

07 · integration recipe

Refuse to fabricate a Metkagram object when a requested stable Pattern ID does not exist.

/api/v1/patterns/metkagram-does-not-exist.json

Lookup: {"pattern_id":"METKAGRAM-DOES-NOT-EXIST"}

• say that no reviewed object was found
• do not invent a stable ID, formula, provenance, or canonical URL
• optionally fall back to discovery or the public pattern index without claiming an exact match