finance-research-agent: Skill for Claude Code

.claude/skills/management-credibility/SKILL.md

management-credibility is a skill for Claude Code from sreenathvemula/finance-research-agent. It costs 113 tokens per session (1,510 once invoked), scanned A, original, Apache-2.0.

A review method for checking whether company managers deliver on promises made during earnings calls, which are meetings where companies discuss financial results and future plans.

In plain words
What is it for?
Use it to review guidance about revenue growth, profit margins, spending, and outlook across several quarters, then measure accuracy and variance against actual sales, operating profit, net profit, and earnings per share.
Why use it?
It replaces a general impression of management with a comparison between past forecasts and reported results. It also examines hedging or evasive language around missed targets, while noting when call data is unavailable.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is sreenathvemula/finance-research-agent's own configuration. It tells Claude Code how to work on finance-research-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything finance-research-agent configures →

Reuse

Borrowing it

Nothing to install: this file belongs to sreenathvemula/finance-research-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/sreenathvemula/finance-research-agent/main/.claude/skills/management-credibility/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/sreenathvemula/finance-research-agent

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,510 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00113 $0.01510
Opus 5 $0.00056 $0.00755
Sonnet 5 $0.00023 $0.00302
Haiku 4.5 $0.00011 $0.00151

Measured 10d ago against content hash 7d61a80cdbcf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

management-credibility 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 10d 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.

.claude/skills/management-credibility/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Management credibility

Trust is earned by delivery. This skill compares what management PROMISED against what the company REPORTED, scores the gap with a precise, repeatable methodology (not a vibe), and reads the language around misses for evasiveness patterns — so the user can judge credibility on evidence, not tone alone.

Procedure

  1. Resolve the symbol; note the company type — guidance style differs materially (IT services guide revenue-growth ranges and margin bands; manufacturers guide capex and capacity; banks guide credit growth, NIM and credit-cost).

  2. Pull both sidesmanagement_guidance (default lookback_periods=6; use 8-10 for a fuller track record). It returns:

    • dated forward-looking / guidance statements retrieved from past concalls (revenue-growth, margin, capex, outlook themes), and
    • the actual reported quarterly results (Sales, OPM %, Net Profit, EPS). If concalls aren't indexed for the company, it says so and still returns the actuals — note the limitation and don't force a credibility verdict off actuals alone.
  3. Score each guidance instance with a precise variance band, not a loose "close enough": Variance % = (Actual - Guided) / |Guided| × 100 (for a guided range, compare against the nearer band edge; for a directional guide with no number — e.g. "margins should improve" — score it qualitatively as met/missed against the reported change, and say you did).

    • Beat: actual exceeds guidance by >5%
    • Met: actual within ±5% of guidance
    • Modest miss: actual below guidance by 5-15%
    • Large miss: actual below guidance by >15%, or guidance quietly dropped/revised down without being flagged as such by management Tabulate every instance found — don't cherry-pick the clean ones.
  4. Compute the summary scores:

    • Hit rate = (instances scored Met or Beat) / (total instances) over the lookback window — state as e.g. "6/8 quarters (75%)".
    • Directional accuracy vs magnitude accuracy — separate "called the right direction but missed the size" (e.g. guided "modest growth", delivered 2% when they meant closer to 8%) from "called the wrong direction entirely" (guided growth, delivered a decline). The latter is materially worse for credibility than the former.
    • Sandbagging vs over-promising pattern — check whether misses cluster as chronic over-promising (repeated large misses, same direction every time) vs chronic sandbagging (guidance consistently beaten by a wide, suspiciously consistent margin — itself a credibility flag, since it implies guidance is being lowballed rather than genuinely forecast).

Read the full file on GitHub · 98 lines

Changes

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.

  1. 10d ago First seen · 98 lines · 113 tokens per session scan A 7d61a80cdbcf

Subscribe to this mod's changes

management-credibility is a skill published in the GitHub repository sreenathvemula/finance-research-agent (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 113 tokens to every session and 1,510 once invoked, about $0.0006 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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