call-summarizer
Turn a finished CALL-E phone-call transcript into a structured post-call brief with a one-line outcome, a masked summary, extracted action items with owners and due dates, caller sentiment, and a redacted caller fingerprint. Use after any CALL-E call when an agent or operator nee
Profil aset
Riset dan pekerjaan pengetahuan
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Skenario
Agent riset
I need my agent to research a topic, compare sources, and produce a concise report.
Kecocokan Agent
Claude Code + CLI + Codex
Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.
Pasang
Siap
npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizer
Pemeliharaan
Terkini
2 hari sejak push
Risiko
Perlu ditinjau
Dependency or permission surface needs review
Kualitas GitHub
63
65/100 Kualitas · 66/100 Kepercayaan
Tag cakupan
Catatan ulasan
Dependency or permission surface needs review · Permission surface may require sandboxing
Kartu adopsi Agent
Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat
Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.
Kualitas
MenjanjikanUseful candidate, but compare it with alternatives before adopting.
Kepercayaan
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Perlu ditinjauTinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Trust Score OpenAgentSkill v5
Tinjauan manusia sebelum pemasangan
Choose a stronger alternative or inspect the source manually before any install attempt.
Star
63 star GitHub
Aktivitas repositori
63 star dan 127 fork
Pemeliharaan
2 hari sejak push
Lisensi
MIT
Pasang
npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizer
Keamanan pemasangan
Jalur pemasangan paket atau runtime standar
Cakupan izin
shell or command execution, filesystem or document access
Hasil Agent
Belum ada data hasil Agent
Dokumentasi
Konteks README/SKILL.md kuat
Ringkasan risiko
Tinjau sebelum produksi
- The skill relies on regex-based masking for personal names, which is explicitly partial and may miss names without introduction cues. This is documented, but downstream consumers should be aware of the limitation.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
Kesiapan pemasangan
Jalur pemasangan tersedia
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Lisensi dinyatakan
- Belum ada bukti hasil Agent-Proven
Metadata yang dapat dibaca Agent
Data keputusan yang dapat dibaca mesin untuk skill ini.
Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.
Tugas yang sesuai
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
- Sumber pencarian
Agent yang sesuai
Keputusan pemasangan
- Perintah
- npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizer
- Kebijakan
- Tinjau
- Tinjauan manusia
- Ya
Kepercayaan dan risiko
- Kepercayaan
- 58/100
- Audit
- 74/100
- Tingkat risiko
- Perlu ditinjau
Lingkar hasil
- Endpoint
- /api/agent/outcome
- ID event
- resolve
- Hasil
- 5
Perintah pemasangan
npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizerJangan gunakan ketika
- Tim yang membutuhkan SLA dengan dukungan vendor
- production agents without a repository review
- The skill relies on regex-based masking for personal names, which is explicitly partial and may miss names without introduction cues. This is documented, but downstream consumers should be aware of the limitation.
- Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
- Dependency or permission surface needs review
Skill alternatif
Last30days Skill
53.5K Star
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Skill alternatif
Academic Research Skills
38.4K Star
npx skills add Imbad0202/academic-research-skills
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GPT Researcher
28.0K Star
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Star
npx skills add Alibaba-NLP/DeepResearch
Keamanan Agent v2
42/100 · Hindari pemasangan otomatis
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Tinggi
Eksekusi shell atau perintah
Metadata skill merujuk terminal, CLI, shell, subprocess, atau alur kerja eksekusi perintah.
Sedang
Akses jaringan
Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.
Sedang
Akses sistem file
Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.
Sedang
Akses database
Skill dapat memeriksa skema, mengkueri database, atau bekerja dengan penyimpanan persisten.
- Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
- Dependency or permission surface needs review
Target pemasangan
Pasang skill ini di alur Agent Anda
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install calle-ai-call-summarizerRencana resolusi Agent
Biarkan Agent memverifikasi kecocokan sebelum memasang.
API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.
Buka JSON
/api/agent/resolve?task=Use%20call-summarizer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20call-summarizer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/calle-ai-call-summarizer/install
Agent harus memeriksa
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Salin prompt
Task: Use call-summarizer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20call-summarizer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/calle-ai-call-summarizer/install
Install command: npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Serah-terima Agent
Berikan jalur pemasangan kepada Agent, bukan direktori lain.
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
Serah-terima pemasangan
/api/skills/calle-ai-call-summarizer/install
Format teks LLM
/api/skills/calle-ai-call-summarizer/install?format=text
Cari alternatif
/api/skills/search?q=call-summarizer&limit=3
Prompt Agent
Use call-summarizer for this task. Review https://www.openagentskill.com/api/skills/calle-ai-call-summarizer/install, then install with: npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizerMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/calle-ai-call-summarizer
Teks LLM
/api/registry/manifest/calle-ai-call-summarizer?format=text
Alias pemasangan
/api/registry/install/calle-ai-call-summarizer
Rekomendasikan
/api/registry/recommend?task=Use%20call-summarizer%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
Agent riset
Tag use case
Platform
Claude Code
Laporan audit
Perlu ditinjau · 74/100
Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Panel keputusan Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Peran di stack
Kandidat cadangan
Kecocokan utama
Agent riset
Label kepercayaan
Buat prototipe dulu
Jalur pemasangan
Perintah siap
Gunakan saat
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
Bukti
- recent repository activity
- install command or GitHub repo available
- profil kualitas 65/100
- 5 event interaksi OpenAgentSkill
tinjau dulu
- The skill relies on regex-based masking for personal names, which is explicitly partial and may miss names without introduction cues. This is documented, but downstream consumers should be aware of the limitation.
Jalur implementasi
- 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil kepercayaan
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adopsi GitHub
Periksa63 star GitHub
Aktivitas star/fork
Periksa63 star dan 127 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus2 hari sejak push
Kejelasan lisensi
LulusMIT
Sinyal positif
- Tinjauan AI disetujui
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Repositori yang baru dipelihara
- Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
- Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama
Tinjau sebelum memasang
- The skill relies on regex-based masking for personal names, which is explicitly partial and may miss names without introduction cues. This is documented, but downstream consumers should be aware of the limitation.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 127 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, external package install surface
- Permission surface: shell or command execution, filesystem or document access
- Belum ada laporan hasil Agent nyata
- Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan
Tindakan yang disarankan
Choose a stronger alternative or inspect the source manually before any install attempt.
Profil kualitas
Menjanjikan kandidat untuk alur kerja Agent
Useful candidate, but compare it with alternatives before adopting.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Daftar alternatif
Bandingkan sebelum memasang
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Ringkasan
--- name: call-summarizer description: Turn a finished CALL-E phone-call transcript into a structured post-call brief with a one-line outcome, a masked summary, extracted action items with owners and due dates, caller sentiment, and a redacted caller fingerprint. Use after any CALL-E call when an agent or operator needs an actionable, reviewable record of what was said without re-reading the whole transcript or re-playing the recording. license: MIT ---
# Call Summarizer
Use this skill after a CALL-E call has completed and the agent needs to turn the returned transcript into a compact, actionable post-call record.
`call-summarizer` is a post-call analysis skill. It takes a CALL-E call result that already contains a transcript, runs locally with no additional phone calls and no network access, and emits a single structured brief: a one-line outcome, a masked summary of the conversation, the action items with owners and due dates, the caller sentiment, and a redacted caller fingerprint for dedup.
It is a good fit for CALL-E's design: the hard part (the call) is already done, and the remaining work (turning a long transcript into something an agent can act on) is pure text analysis that should not require a second provider or a paid summarization API.
## When To Use
Use this skill for:
- turning a completed CALL-E call transcript into a one-page post-call brief - extracting action items with owners and due dates from a call - surfacing caller sentiment so a follow-up can be triaged correctly - producing a masked summary that is safe to log, store, or hand to a human - building a redacted caller fingerprint for de-duplicating repeat callers - any workflow where the call is done and the record is the deliverable
## When Not To Use
Do not use this skill to:
- place, schedule, or cancel a phone call; it only reads transcripts - summarize a call that has no transcript; it will abstain instead of inventing one - act on the action items; it reports them, the operator decides whether to execute - store PII; every output is masked and the fingerprint is one-way hashed - replace a human review for medical, legal, financial, or emergency content - run during the call; it is strictly post-call and never affects call behavior
## Workflow
### 1. Collect the call result
Required: a CALL-E call result containing a `transcript` field (the full dialogue turns between the agent and the callee). The transcript may be plain text or a list of turns; both are handled.
Confirm with the operator that this transcript belongs to a call they authorized and that they want a post-call brief generated. Never run this skill on a transcript whose origin is unknown.
### 2. Generate the brief locally
Run `scripts/summarize_call.py` on the transcript. By default it reads from a file path and prints the brief to stdout; it makes no network calls and places no calls.
```bash python3 scripts/summarize_call.py --transcript path/to/transcript.json --out brief.json ```
The script performs:
1. **Outcome line**: a single sentence stating the call result (confirmed, declined, rescheduled, no-answer, voicemail, unknown) using only words that appear in the transcript. The outcome is bound to the callee's latest effective response (agent text never counts as a confirmation), and any contradictory intent — across utterances or within a single utterance (e.g. "Yes, I can't make it") — fails closed to `unknown`. 2. **Masked summary**: a short prose summary with phone numbers, emails, account identifiers, and title-prefixed or cue-introduced personal names replaced by masked tokens. The brief sets `masked: "partial"` with a `masking_scope` field documenting exactly which PII classes are tokenized; ordinary personal names without an introduction cue are NOT redacted (the skill uses no NER model and the contract is honest about this boundary). 3. **Action items**: each commitment, follow-up, or next step extracted with an owner (the party who said they would do it), a verb, and an optional due date parsed from natural-language time references. Ambiguous items keep `owner: unknown` rather than guessing. 4. **Sentiment**: a coarse label (`positive`, `neutral`, `negative`, `mixed`) with a short justification span from the transcript. It never reports a sentiment the transcript does not support. 5. **Caller fingerprint**: a one-way hash of a stable caller identity input (the masked caller phone number, or an explicit `caller_id` field if provided). The `call_id` is deliberately excluded so the same caller produces the same fingerprint across calls, enabling de-duplication without storing PII.
### 3. Validate the brief
Run `scripts/validate_brief.py` to confirm the brief is well-formed before any downstream system consumes it. It checks that every action item has an owner, that masking has no residual raw phone numbers, emails, account identifiers, or personal names, and that the outcome line is non-empty and grounded in the transcript.
### 4. Review or route
Return the brief to the operator or the calling agent. The skill does not execute any action item; it only reports them. Routing decisions (escalate, follow up, close the ticket) stay with the operator or the host agent.
## Output Schema
The brief is a single JSON object:
```json { "outcome": "Appointment confirmed for Tuesday 10:00.", "summary": "The callee confirmed the appointment and asked for a reminder the day before.", "actions": [ { "owner": "agent", "verb": "send reminder", "due": "2026-09-15", "source_span": "I will send a reminder the day before." } ], "sentiment": { "label": "positive", "justification": "Callee confirmed without hesitation." }, "caller_fingerprint": "sha256:9f2c...", "masked": "partial", "masking_scope": "phone_numbers emails account_ids title_prefixed_names cue_introduced_names", "masking_note": "Structured PII and cued personal names are tokenized. Ordinary uncued names are NOT redacted." } ```
## Safety Rules
Read `references/safety.md` for the full safety contract.
- This skill never places a call and never modifies call state. - Every output is partially masked: phone numbers, emails, account IDs, and cued personal names are tokenized. The `masked` field is `"partial"` with a `masking_scope` documenting the boundary; ordinary uncued names are NOT redacted (no NER model). - The caller fingerprint is a one-way hash; the raw identity is never stored. - Action items are reported, not executed. Medical, legal, financial, and emergency commitments are flagged as `category: sensitive` and routed to a human rather than auto-dispatched. - If the transcript is empty, garbled, or does not support an outcome, the skill abstains with `outcome: unknown` and an empty `actions` list. It never invents a plausible outcome. - No PII leaves the local process. There is no network call and no third-party summarization API.
## Requirements
- Python 3.9 or newer. The skill uses only the Python standard library, so no `pip install` is required for the default (no-call) path. - A CALL-E call result with a transcript. Live calls are out of scope; see the `call-reminder` or `verify-by-phone` skills for placing calls.
## Quick Start
```bash # Dry run on the bundled example transcript (no calls, no network). python3 scripts/summarize_call.py \ --transcript references/example-transcript.json \ --out /tmp/brief.json
# Validate the brief. python3 scripts/validate_brief.py --brief /tmp/brief.json ```
## Examples
See `references/examples.md` for worked examples on different call types (confirmation, reschedule, no-answer, voicemail) and the expected brief for each.
Detail teknis
- Versi
- 1.0.0
- Lisensi
- MIT
- Pembaruan terakhir
- 21 Agu 2026
- Diterbitkan
- 21 Agu 2026
Ringkasan keputusan
Kandidat cadangan
recent repository activity
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 73/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- Tingkat sukses
- —
- Kegagalan terbaru
- —
- Hasil
- 0
- Kualitas output
- —
- Gagal
- 0
- Tidak relevan
- 0
- Pemasangan
- 0
- Diblokir risiko
- 0
- Perlu penyiapan
- 0
- Produksi
- 0
Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.
Pasang
Tambahkan ke alur Agent
Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.
Siklus pertumbuhan
Kit berbagi
Draf berbasis skenario untuk call-summarizer, siap untuk posting manual di X.
call-summarizer: Turn a finished CALL-E phone-call transcript into a structured post-call brief with a one-lin... 63 stars https://www.openagentskill.com/skills/calle-ai-call-summarizer?ref=x
Balasan opsional dengan perintah pemasangan
Listing + install path for call-summarizer: https://www.openagentskill.com/skills/calle-ai-call-summarizer?ref=x Install: npx skills add CALLE-AI/awesome-phone-call-agents --skill call-summarizer
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- CALLE-AI
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim pemilik
Klaim listing skill ini
Listing Diindeks Registry ini dikaitkan dengan CALLE-AI, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.
Kit backlink kreator
Tambahkan badge bukti ke README Anda
Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.
[](https://www.openagentskill.com/skills/calle-ai-call-summarizer)
[](https://www.openagentskill.com/skills/calle-ai-call-summarizer)
[](https://www.openagentskill.com/skills/calle-ai-call-summarizer/audit)
[](https://www.openagentskill.com/skills/calle-ai-call-summarizer)Penulis
CALLE-AI
@calle-ai
Tag
Kecocokan platform
Sinyal kesehatan
- Star GitHub
- 63
- Skor kualitas
- 36/100
- Push GitHub terakhir
- 21 Agu 2026
- Petunjuk framework
- Tidak diketahui
- Tampilan OpenAgentSkill
- 5
- Salinan pemasangan
- 0
- Klik keluar
- 0
Sinyal komunitas
Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.
Kepercayaan & keamanan
Do not auto-install
- Adopsi GitHub63 star GitHubPeriksa
- Aktivitas star/fork63 star dan 127 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
- Pemeliharaan terbaru2 hari sejak pushLulus
- Kejelasan lisensiMITLulus
- Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
- Risiko dependensi/runtimecommand execution surface, external package install surfacePeriksa
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