Speaking coach

Speaking Coach

Terminal-friendly speaking practice: record or perform → transcribe → evaluate. Paths are relative to ${CLAUDE_PLUGIN_ROOT} (if unset, resolve relative to the plugin root — the directory two levels above this file, .../plugins/english-exam-coach).

When to use

The user wants a speaking task, mock speaking interview, or feedback on an answer they spoke (pasted as transcript or provided as an audio file).

Steps

1. Identify exam + level + part. Load data/exam-formats/<exam-id>.md, data/cefr/speaking-descriptors.md, and data/cefr/speaking-calibration-anchors.md (leveled transcript samples). Seed shapes: data/item-bank/seed/speaking-tasks.md (imitate format, never reuse).

2. Generate the task with the exam's real prep/speaking times (e.g. IELTS Part 2: 1 min prep, 1–2 min talk; TOEFL interview answers: 45 s each with no preparation time). Pitch the prompt's demand to the level (B1 concrete/personal; B2 opinion on a familiar topic; C1 abstract, asks the speaker to weigh/hypothesise; C2 nuanced) — speaking-calibration- anchors.md shows an at-level answer to aim the prompt at. Visual-dependent tasks (Cambridge B1 Part 2 describe-a-photo; B2 First / C1 Advanced Part 2 compare-photographs; C2 Part 2 picture discussion) can't be rendered here; say so and offer a non-visual part instead of faking it. IELTS Speaking uses no visual prompts — its Part 2 is a text cue card and IS fully renderable. Tell the user how to respond, in order of preference:

   • record themselves (any voice recorder) and paste an accurate transcript, noting hesitations/self-corrections honestly;
   • or speak first and then type from memory (say that this loses fluency information);
   • for a paired-format task (collaborative discussion), play the partner: alternate short turns with the user in chat.

   TOEFL Listen and Repeat (7 of the 11 TOEFL speaking items) works differently: deliver each sentence once via say when available (else read it once as a partner), have the user repeat it from memory and type what they said, and score each sentence on exactness — content words, word order, grammatical endings. Report the sentence length at which recall broke down; that breakdown point is itself the diagnostic. Log with --task-type toefl-listen-and-repeat --score <n> --max 7.

3. Evaluate the transcript against the five paraphrased CEFR aspects (range, accuracy, fluency, interaction, coherence) and the exam's criteria structure. Calibrate before fixing a range: place the transcript next to the nearest level in speaking-calibration-anchors.md per aspect (aspects may land on different levels — say so). The anchors start at B1: if the transcript sits clearly below the B1 anchor on most aspects, report it as below B1 (approx. A1/A2) rather than snapping up to B1, and log --level / --cefr-estimate as A1 or A2 accordingly. From text alone, fluency and pronunciation are only partly observable — judge fluency from fillers/self-corrections if the transcript preserves them, and say so; only comment on pronunciation the user asks about or reports ("I struggle with th-").

4. Return: (a) estimate as a range + CEFR level; (b) 3–5 prioritized fixes with your phrase → stronger phrase rewrites from the user's own answer; (c) one upgraded model answer fragment (2–3 sentences, next level up); (d) one follow-up question to re-drill the weakest point now.

5. Log the attempt (silently):

   python3 "${CLAUDE_PLUGIN_ROOT}/skills/progress-tracker/scripts/log_attempt.py" \
     --exam <exam-id> --skill speaking-coach --task-type <slug> \
     --level <anchor> --band-estimate "<low>-<high>" --cefr-estimate <cefr> \
     --seconds <time-on-task>
   

   On Windows, if python3 isn't found, use python or py instead. Use the exact --task-type slug from data/task-types.md. Add --criteria "fluency=B2,lexis=B2,grammar=B1,..." with the per-aspect levels you just judged, and be honest about the evidence: --evidence-grade partial for a transcript typed from memory (the content survived, the delivery did not), full only when it came from audio.

6. Run the clock, and close the loop. For a timed task, run it under the real exam clock instead of "start when ready" — that constraint is most of the task's difficulty:

   python3 "${CLAUDE_PLUGIN_ROOT}/skills/progress-tracker/scripts/timed_speak.py" \
     --exam <exam-id> --task <slug>
   

   It prints the seconds to log and --timing-source script. Afterwards log 2–5 mistakes with log_error.py, run queue.py sync, and offer a second attempt at the same task, reporting the per-aspect delta. Full protocol: ../progress-tracker/references/the-loop.md. For TOEFL estimate the 1–6 band scale: --score <band> --max 6 (half bands allowed; official CEFR alignment: 4 ≈ B2, 5 ≈ C1, 6 = C2).

Boundaries

• Never claim to hear audio you cannot access; if an audio file is provided and cannot be transcribed in this environment, ask for a transcript instead of inventing one.
• Descriptors are paraphrased public CEFR only; no official rubrics.
• Estimates are indicative ranges, never official scores.
• Do not log attempts the user didn't make.