AI Language Learning Cookbook

01 · AI workflow

Find a pattern for what you want to say

Use Metkagram as the source. I want to disagree politely. Find the closest reviewed pattern, keep its stable ID and canonical URL, explain why it fits, then ask me to write my own example.

02 · AI workflow

Improve my sentence with a canonical pattern

Use Metkagram to analyse my sentence. Find the closest published pattern, cite its stable ID and canonical URL, explain the difference, then suggest one revision that preserves my meaning.

03 · AI workflow

Practise retrieval before feedback

Choose one B2–C1 Metkagram pattern. Give me a realistic situation first and hide the formula until I answer. Then grade my attempt against the canonical pattern and cite it.

04 · AI workflow

Compare two nearby constructions

Find two related Metkagram patterns for the same communicative move. Compare meaning, register and context. Keep both stable IDs and canonical links in the answer.

05 · AI workflow

Practise English–German transfer

Use reviewed Metkagram cross-language records. Show how the same communicative move is realised in English and German, cite canonical IDs, then ask me to produce both versions.

06 · AI workflow

Build a ten-minute lesson

Build a 10-minute B2–C1 lesson using published Metkagram objects: 3 patterns, one contrast and one retrieval task. Preserve stable IDs and canonical URLs.

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