Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/makingchatbots/genesys-cloud-plugins/interpret-flow-irnpx skills add MakingChatbots/genesys-cloud-plugins --skill interpret-flow-irgit clone --depth 1 https://github.com/MakingChatbots/genesys-cloud-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00235 | $0.05043 |
| Opus 5 | $0.00118 | $0.02521 |
| Sonnet 5 | $0.00047 | $0.01009 |
| Haiku 4.5 | $0.00023 | $0.00504 |
Grade A, and why
interpret-flow-ir scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interpreting Flow IRs
The flow_ir tool returns a deployed flow's intermediate representation (IR):
the flow parsed into an explicit control-flow graph, flattened to a node list.
Branches, loops, IVR menu choices, and cross-task jumps are already resolved
into edges. Answer structural questions from this IR, never by re-deriving
control flow from the flow's raw configuration JSON.
The tools are a trio. search_in_flow owns discovery — which actions mention a
given name, expression, or phrase (see "Content search"). flow_ir owns
structure — what connects to what. flow_action owns semantics — what an
individual action is configured to do (see "Action semantics"). The usual order
runs the same way: search to find the ids worth caring about, trace to see how
they connect, then inspect only those.
All three take a flow id, not a flow name. When only the name is known (e.g.
"analyse Book_Payment"), resolve it first with find_flow, which searches flow
names and returns each match's id, name, type, and published version.
Tool output shape
On success the tool returns compact JSON: { flowId, ir, warnings }. Failures
(flow not found, unparseable configuration, unknown or ambiguous task value)
arrive as plain-text tool errors, so any JSON response is a successful parse.
warnings is always present; read it before making claims, because each
warning scopes what can be asserted (see "Warnings").
ir fields:
| Field | Meaning |
|---|---|
flowName, flowType |
Flow identity (e.g. inboundcall, digitalbot) |
entryTaskId |
The flow's entry task, when known. Absent when the flow declares no entry or the declared entry is unresolvable (UNRESOLVED_INITIAL_SEQUENCE). Do not fall back to tasks[0], which is then just declaration order |
reachabilityIsComplete |
false when the flow contains intent listen actions whose routing is unmodelled (UNRESOLVED_INTENT_FANOUT). When false, treat every reachable: false as "not provably reachable", never "dead" |
tasks |
Task list { id, name, reusable }. reusable: true marks tasks flagged reusable in Architect |
nodes |
Flat node list, sorted ascending by order |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 340 lines · 235 tokens per session scan A 745b54c58263
interpret-flow-ir is a skill published in the GitHub repository MakingChatbots/genesys-cloud-plugins (9 stars, last pushed 2d ago), licensed MIT. It adds 235 tokens to every session and 5,043 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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