call-agent-commitment-tracker

An agent that says "I'll send that right away" and doesn't — is worse than one that said nothing.

When an automated agent makes a call, it often commits to future actions: sending a confirmation email, having a specialist call back, filing a referral. Those commitments are audible, remembered by the person, and completely untracked unless this skill reads the transcript.

This is the post-call layer: it reads the finished get_call_run transcript, extracts every agent commitment, classifies it by urgency, and hands you a ready-to-use follow-up call goal to verify fulfillment.

When To Use

• after any CALL-E call where the agent may have made forward-looking promises
• as part of a quality-assurance pipeline to prevent "ghost commitments"
• before a follow-up call to understand what the previous call committed to
• in collection, healthcare, or support workflows where broken commitments carry legal or reputational risk

When Not To Use

• to audit the callee's promises (this skill only tracks agent turns)
• during a call; strictly post-call analysis plus pre-call goal crafting
• as a definitive legal record; it is heuristic and advisory only
• to replace CRM or ticketing systems for obligation tracking

Workflow

Audit a finished call

python3 scripts/commitment_tracker.py analyze \
  --transcript path/to/call-result.json

Reads the real get_call_run result shape ({status, result: {transcript}}) or the flat fixture shape used by sibling skills. Emits a commitment card:

• commitments[]: each detected commitment with turn_index, classification, and evidence (PII-masked, capped at 200 chars)
• commitment_count: counts by WITH_DEADLINE, WITHOUT_DEADLINE, CONDITIONAL
• verdict: COMMITMENTS_FOUND / NONE_FOUND, plus unclear paths (empty transcript, no agent turns)
• recommended_action: schedule_followup_call with guidance, or no_followup_required
• disclaimer: heuristic advisory disclaimer on every card

Commitment classifications

Class	Description	Examples
WITH_DEADLINE	Commitment with explicit time window	"within 30 min", "by end of day", "ASAP", "right away"
WITHOUT_DEADLINE	Open-ended pledge	"I will follow up", "we will send"
CONDITIONAL	Pledge contingent on callee action	"I will if you confirm", "once you approve"

Callee turns are always excluded

The skill only scans AGENT turns (speakers not in callee / customer / patient / caller / recipient / user). A callee saying "I will think about it" is never recorded as an organization commitment.

Craft the follow-up call goal

python3 scripts/commitment_tracker.py craft --scenario commitment-followup

Emits the plan_call inputs JSON whose goal instructs the next call to: verify whether the promised action was carried out, acknowledge any gap without blame, and escalate to a human colleague if needed — without making new commitments itself.

Scientific Foundation

Research	Relevance
Searle, J.R. — Speech Acts: An Essay in the Philosophy of Language (Cambridge Univ. Press, 1969)	Taxonomy origin of Commissive acts — utterances that commit the speaker to a future action; the theoretical basis for the classification in this skill
Austin, J.L. — How to Do Things with Words (2nd ed., Oxford Univ. Press, 1975)	Foundational theory of performative utterances; commissives are one of five illocutionary act classes
Burdisso et al. — Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction (EMNLP 2024, arXiv:2410.18481)	Methodology for mapping utterances by communicative function; commitment extraction is a direct application of the commissive-action region
Choubey et al. — Turning Conversations into Workflows: A Framework to Extract and Evaluate Dialog Workflows for Service AI Agents (Salesforce AI Research, ACL 2025, arXiv:2502.17321)	Empirical validation of extracting procedural commitments from customer-agent transcripts; confirms the practical grounding of this skill
SemEval-2025 Task 6 — PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification (ACL Anthology 2025, aclanthology.org/2025.semeval-1.321)	The most recent benchmark for promise detection and verification; provides taxonomy and evaluation methodology directly applicable to this skill

This skill implements a lexical/regex heuristic that operationalizes the commissive-speech-act class. It does not use model internals and labels every output analysis_mode: "heuristic".

Differences from sibling skills

• call-cross-call-consistency-checker compares stated facts across two calls for contradictions; this skill tracks future-action pledges within one call.
• call-review audits general call quality and compliance; this skill specializes exclusively in forward-looking agent commitments.
• call-agent-certainty-calibrator grades how confidently the agent stated facts; this skill grades whether the agent made promises it should follow up on.