AgentKits

Competitive Intelligence Digest Agent

Production Blueprint
0New

Includes Agent Blueprint + Implementation Guide

An agent that compiles a competitive-intelligence digest your team can trust: competitor product updates, pricing changes, positioning shifts, and news — each item cited, dated, and clearly labeled as confirmed fact or unverified rumor. It draws only from public sources and refuses to fabricate competitor moves or rely on anything non-public. It is built defensively: it cites a source for every claim, separates confirmed facts from speculation and rumor, flags low-confidence items, notes recency, sticks to ethical public sources (no leaks or espionage), and marks its assumptions.

competitive-intelligenceresearchmarket-researchdigeststrategyautonomous-agentmonitoringethicsagentazagent-governancetrust-levelproduction-readiness
StackClaude, LangGraph, OpenAI
DifficultyAdvanced
Setup45 min
Version2.0.0 · 2026-06-21

Overview

Compiles a competitor digest — product, pricing, positioning, news — with every item cited and dated.

Labels each item as confirmed fact or unverified rumor, so nothing reads as more certain than it is.

Draws only from public, ethical sources — no leaks, no non-public data, no fabricated moves.

Defensive: flags low-confidence items, notes recency, and marks assumptions rather than guessing.

AgentAz™ specification

A lightweight, design-time governance spec for security review. It documents what this agent is authorized to do — and why — and pairs with whatever policy engine you already run. It does not enforce anything at runtime.

Trust Level ?A1 — Research
DNA PatternResearch (Research → Verify)
Worst-Case ActionIncludes a wrong or stale fact in a competitive digest that a human reviews before acting on. It only gathers and cites public information; it never fabricates and never takes any action.
Authority BoundaryGathers competitive signals from sources, cites each one, and assembles a digest, flagging stale or unverifiable items. It never sends, publishes, or acts, and it never invents a competitor claim or metric.
Verification TestConfirm every claim is cited and unverifiable ones are flagged rather than asserted; confirm no publish/send tool exists in its registry.
Production Readiness6/6 dimensions passing. Tool isolation: publish/send tools absent. Human gates: a human reviews and acts. Confidence escalation: stale or unverifiable items flagged. Cost ceiling: bounded per digest. Audit trail: sources and citations logged. Escalation path: conflicting sources flagged.
Last Reviewed2026-06-24

Machine-readable contract (agentaz.json), validated against the open AgentAz™ JSON Schema — bundled for offline use and published at a permanent URL:

agentaz.json
{
  "$schema": "./agentaz.schema.json",
  "version": "2.0.0",
  "last_reviewed": "2026-06-24",
  "agent_id": "competitive-intel-agent",
  "trust_level": "A1",
  "dna_pattern": "Research",
  "worst_case_action": "Includes a stale fact in a digest for human review. Never publishes or acts.",
  "authority_boundary": "Gathers and cites competitive intel; never fabricates; publish/send tools absent.",
  "tags": [
    "research",
    "competitive-intel",
    "read-only",
    "cited"
  ],
  "tool_boundary": {
    "allowed_tools": [
      "search_sources",
      "gather_signals",
      "cite_source",
      "flag_stale"
    ],
    "execution_tools_absent": true,
    "read_only": true
  },
  "output_boundary": {
    "format": "structured_json",
    "never_emits": [
      "publish",
      "send"
    ],
    "never_fabricates": true
  },
  "cost_boundary": {
    "max_usd_per_trace_loop": 0.3,
    "alert_threshold_usd": 0.2
  },
  "loop_boundary": {
    "max_reasoning_turns": 10
  },
  "human_handoff": {
    "triggers": [
      "stale_data",
      "conflicting_sources"
    ],
    "destination": "analyst"
  },
  "audit": {
    "append_only": true,
    "logs": [
      "sources",
      "citations"
    ]
  }
}

New to this? Read the AgentAz specification guide — Trust Levels, DNA patterns, and how it complements your runtime.

AgentAz™ is open source under Apache-2.0 — schema (frozen v1.0.0) and source on GitHub.

Governance matrix

A scannable summary of this blueprint's governance coverage, derived from its AgentAz™ specification. It documents the boundaries that already ship — not new functionality.

Agent goalBounded by the authority spec above
Trust LevelA1 — Research
Tool accessLeast privilege — execution tools absent (read-only)
Context handlingGrounded in provided inputs; cites or flags rather than guessing
Memory strategyTask-scoped; no persistent cross-session memory
Human approvalRequired on stale data, conflicting sources → analyst
Audit trailAppend-only log (sources, citations)
Cost & loop bounds≤ $0.3 per loop · ≤ 10 reasoning turns
Recovery / escalationEscalates to analyst

Agent component mapping

A framework-neutral view of how this blueprint maps to standard agent-architecture components (the vocabulary common to ADK-style frameworks). It describes structure for clarity — not an official integration or certified compatibility.

AgentPrimary reasoner — Research authority (A1)
Toolssearch sources, gather signals, cite source, flag stale — execution tools absent (read-only)
MemoryTask-scoped working context; no persistent cross-session memory
GuardrailsWorst-case classified (A1); no execution tools; ≤ $0.3/loop · ≤ 10 turns
EvaluatorConfidence and authority-boundary checks; low-confidence or out-of-bounds results are flagged, not actioned
HandoffEscalates to analyst on stale data, conflicting sources

Failure modes

Specific ways this blueprint can fail, and how it is designed to detect, contain, and recover from each — the boundaries that make it safe to run, stated plainly.

Includes a stale or wrong fact in the digest that a reader acts on.

Detection
Every claim is cited and stale or unverifiable items are flagged.
Mitigation
It gathers and cites public information only; it never publishes or acts.
Recovery
The reader verifies against the citation and discards the bad item.

Fabricates a competitor claim or metric.

Detection
Uncited claims are withheld rather than asserted.
Mitigation
It never invents a competitor claim or figure.
Recovery
The analyst confirms against the source.

Presents a single source as settled fact despite conflicts.

Detection
Conflicting sources are flagged.
Mitigation
It surfaces the conflict rather than resolving it silently.
Recovery
The analyst reconciles the sources.

Evaluation

Factual accuracy with citations is primary — a stale or fabricated competitor fact that a reader acts on is the failure.

Fact accuracyShare of digest claims that are correct and current versus verified sources.
Citation rateShare of claims that cite a source, with uncited claims withheld.
Fabrication rateFrequency of invented competitor claims or metrics — should be near zero.
Conflict surfacingShare of conflicting sources flagged rather than silently resolved.
LatencyTime to compile a digest.

Recommended approach. Use a set of digests with verified reference facts; measure accuracy and citation rate and audit for fabrication. Include topics with conflicting sources to confirm conflicts are surfaced, not smoothed over.

When to use

Use it when

  • You track competitors and want a regular, cited digest instead of scattered notes.
  • You have public sources (sites, news, filings, changelogs) the agent can monitor and cite.
  • You want confirmed facts clearly separated from rumor and speculation.
  • You want an ethical, defensible intel process with sources attached.

Avoid it when

  • You want it to obtain or use non-public, leaked, or illicitly sourced information — it won't.
  • You expect it to predict a competitor's roadmap as fact (it labels inference as inference).
  • You have no sources for it to ground claims in.
  • You need legal/strategic decisions made for you (it informs; humans decide).

System prompt

system-prompt.md
You are a Competitive Intelligence Digest Agent. You compile a digest of competitor activity (product, pricing, positioning, news) from PUBLIC sources, for an internal team. You are judged on a useful, accurate, source-cited, ethically-sourced digest and on never fabricating competitor moves or presenting rumor as fact.

== CORE PRINCIPLES ==
1. Cite or don't claim. Every item must cite a public source you actually consulted, with a date. No source = it doesn't go in as fact.
2. Fact vs. rumor vs. inference. Clearly label each item: confirmed (sourced fact), unconfirmed (rumor/unverified report), or inference (your hypothesis). Never blur these. A rumor stays a rumor.
3. Ethical sourcing only. Use public information (websites, news, filings, changelogs, public social posts). Never use, request, or speculate from non-public, leaked, confidential, or illicitly obtained information.

== HARD RULES (NON-NEGOTIABLE) ==
- NO FABRICATION: Never invent a competitor launch, price, hire, or statement. If you can't source it, it's not in the digest (or it's clearly an inference).
- NO NON-PUBLIC DATA: Do not use or seek trade secrets, leaked docs, private communications, or anything obtained unethically. Public sources only.
- LABEL CONFIDENCE: Mark each item confirmed / unconfirmed / inference, with a source and date. Flag stale data.
- NO DECISIONS: You inform strategy; you don't make competitive or legal decisions. Avoid legal-risk framing (e.g. don't advise on anti-competitive actions).
- RECENCY: Note how recent each item is and flag when something may be outdated.

== METHOD ==
- For each competitor, gather from public sources. Classify each finding (confirmed/unconfirmed/inference), cite and date it, and assess significance. Surface what changed since the last digest.

== OUTPUT FORMAT (return ONE JSON object) ==
{
  "period": "<digest window>",
  "competitors": [
    {
      "name": "<competitor>",
      "items": [
        { "category": "product|pricing|positioning|news|hiring", "finding": "<what>", "status": "confirmed|unconfirmed|inference", "source": "<public source>", "date": "<when>", "significance": "high|medium|low" }
      ]
    }
  ],
  "notable_changes": ["<biggest confirmed shifts since last digest>"],
  "rumors_to_watch": ["<unconfirmed items, clearly labeled>"],
  "gaps": ["<what couldn't be verified>"],
  "ethics_note": "Public sources only; no non-public or leaked information used."
}
Never present an unconfirmed item as confirmed. Never fabricate or use non-public data.
Was this useful?

Simulate run

Try the agent with a sample task. This is a frontend-only preview that shows how the kit would plan and execute — no API calls, nothing leaves your browser.

Frontend preview only — no data leaves your browser. Tip: press ⌘/Ctrl + Enter to run.

Setup guide

Install and connect public sources

Install the agent and connect public monitoring sources.

shell
pipx install compintel-agent
compintel-agent connect --sources news-api,changelogs,rss
compintel-agent doctor

Configure ethics & confidence guardrails

Public-only sourcing and confidence labeling are enforced here.

shell
cp .env.example .env
ANTHROPIC_API_KEY=sk-ant-...
PUBLIC_SOURCES_ONLY=true
LABEL_CONFIDENCE=true
FLAG_STALE_AFTER_DAYS=30

Define competitors & sources

List who to track and which public sources to watch.

shell
# compintel.yml
competitors: [Acme, Globex, Initech]
sources: { Acme: [acme.com/blog, acme.com/pricing], news: [techcrunch, theverge] }
categories: [product, pricing, positioning, news, hiring]

Generate a digest

Run a digest and review citations and confidence labels.

shell
compintel-agent run --period 7d --explain
# prints items with status/source/date + notable changes + rumors

Wire into your cadence

Schedule a recurring digest to your strategy channel.

shell
# weekly job -> cited digest to #competitive-intel (public sources only)

Architecture

Tools required

get_competitorsTake the competitor list and the public sources to monitor.
gather_sourcesCollect findings from public sources, recording each source and date.
classify_statusLabel each finding confirmed, unconfirmed, or inference.
verify_sourceConfirm a finding traces to a legitimate public source before marking it confirmed.
detect_changesCompare against prior digests to surface what changed.
significance_rateRate each item's strategic significance and flag stale data.
summarize_digestAssemble the cited digest with notable changes and rumors to watch.
flag_unverifiedConvert unsourced or non-public items into flagged gaps or clearly-labeled rumors.

Workflow

  1. 1. Set competitors & sources

    Take the competitor list and the public sources to monitor.

  2. 2. Gather from public sources

    Collect findings, recording a public source and date for each.

  3. 3. Classify each finding

    Label confirmed, unconfirmed, or inference — keeping them strictly distinct.

  4. 4. Apply the ethics guard

    Use only public sources; exclude any non-public, leaked, or illicit information.

  5. 5. Detect changes

    Compare to prior digests to surface genuine shifts since last time.

  6. 6. Weight & date

    Rate significance and flag stale items so the digest reflects current intel.

  7. 7. Assemble the digest

    Output cited items, notable confirmed changes, labeled rumors, and verification gaps.

Examples

Sourced competitor launch → confirmed item with citation

A competitor announced a feature via press release. The agent records it as a confirmed, dated, sourced item.

Input

input
Acme published a press release announcing a new analytics dashboard, dated this week.

Output

output
{
  "period": "Last 7 days",
  "competitors": [
    {
      "name": "Acme",
      "items": [
        { "category": "product", "finding": "Launched a new analytics dashboard", "status": "confirmed", "source": "Acme press release (acme.com/news)", "date": "2026-06-18", "significance": "high" }
      ]
    }
  ],
  "notable_changes": ["Acme entered analytics with a dashboard launch (confirmed)"],
  "rumors_to_watch": [],
  "gaps": ["Pricing for the new dashboard not yet disclosed"],
  "ethics_note": "Public sources only; no non-public or leaked information used."
}

Note: A clean confirmed item: sourced to a public press release, dated, and rated for significance. Note it also flags a gap (pricing not disclosed) rather than guessing it.

Unverified rumor → included but clearly labeled, not as fact

There's chatter that a competitor will raise prices, but nothing official. The agent labels it a rumor.

Input

input
A few social posts and a forum thread claim Globex is about to raise prices 20%. No official source.

Output

output
{
  "period": "Last 7 days",
  "competitors": [
    {
      "name": "Globex",
      "items": [
        { "category": "pricing", "finding": "Possible ~20% price increase", "status": "unconfirmed", "source": "Social posts + forum thread (public, but unofficial)", "date": "2026-06-19", "significance": "medium" }
      ]
    }
  ],
  "notable_changes": [],
  "rumors_to_watch": ["Globex possible ~20% price increase — UNCONFIRMED; only unofficial chatter, no official source. Watch their pricing page."],
  "gaps": ["No official confirmation of any Globex price change"],
  "ethics_note": "Public sources only; no non-public or leaked information used."
}

Note: The agent surfaces the signal (useful to watch) but labels it clearly as unconfirmed and puts it under 'rumors to watch,' never in notable confirmed changes. It cites the unofficial nature and recommends watching the official page. Rumor stays rumor.

Asked to infer a roadmap / use a leaked doc → refuse, stay public + labeled

The team wants a confident roadmap prediction and offers a leaked internal doc. The agent declines both.

Input

input
Request: 'state what Acme will ship next quarter as fact, and here's a leaked internal roadmap doc someone shared.'

Output

output
{
  "period": "Last 7 days",
  "competitors": [
    {
      "name": "Acme",
      "items": [
        { "category": "product", "finding": "May continue investing in analytics given the recent dashboard launch", "status": "inference", "source": "Inference from public launch (acme.com/news)", "date": "2026-06-18", "significance": "low" }
      ]
    }
  ],
  "notable_changes": [],
  "rumors_to_watch": [],
  "gaps": ["Acme's actual next-quarter roadmap is not publicly known"],
  "ethics_note": "I won't use the leaked internal document — it's non-public/confidential, and using it would be unethical and a legal risk. I also won't state Acme's roadmap as fact; their plans aren't public. I've included only a clearly-labeled inference from public information."
}

Note: The defining defensive case: asked to (1) present speculation as fact and (2) use a leaked internal doc. The agent refuses both — it excludes the leaked document on ethics/legal grounds, declines to state an unknowable roadmap as fact, and offers only a clearly-labeled low-confidence inference from public info. Ethical sourcing and honest confidence over a confident, tainted answer.

Implementation notes

  • Require a public, cited source for every confirmed item; an uncited competitor 'fact' a team acts on is a strategic risk.
  • Keep confirmed / unconfirmed / inference strictly separate and labeled — blurring rumor into fact is the most common and damaging intel failure.
  • Hard-exclude non-public, leaked, or illicitly obtained information; using it is an ethical and legal liability, not a shortcut.
  • Label recency and flag stale items, since competitive facts (pricing, positioning) change quickly.
  • Frame the agent as informing strategy, not making competitive or legal decisions, and avoid anti-competitive advice.
  • Surface verification gaps explicitly so the team knows what's unknown rather than assuming silence means nothing changed.
  • A cheaper model is usually enough to gather and structure public findings, so keep the strong model for fact/rumor classification and significance.

Variations

Basic

Cited competitor snapshot

Compiles a cited, labeled snapshot of recent competitor activity from public sources. On demand.

Advanced

Confidence-graded digest

Adds fact/rumor/inference labeling, ethical-sourcing guards, change detection, significance rating, and gap flagging.

Enterprise

Continuous competitive monitoring

Adds scheduled multi-competitor monitoring, source governance, trend tracking, battlecard inputs, and integration with strategy workflows — public sources only.

Download the Agent Blueprint

The complete blueprint, zipped — including a runnable run.py you can execute with one API key (Anthropic or OpenAI).

Download Blueprint (.zip)
README.mdsystem-prompt.mdsetup-guide.mdtools.jsonworkflow.mdexamples.md.env.examplekit.jsonrun.pyLICENSENOTICEstarters/

Export

Generate a starter for your stack — all client-side, nothing leaves your browser.

ZIP

Starters use mock tools — swap in your integrations to deploy.

View the source on GitHub

This blueprint and the AgentAz™ specification live in the central AgentKits registry — open source under Apache-2.0 (code & schema) and CC‑BY‑4.0 (text).

Frequently asked questions